Digenic inheritance in medical genetics

Digenic variant interpretation with hypothesis-driven explainable AI

The digenic inheritance hypothesis holds the potential to enhance diagnostic yield in rare diseases. Computational approaches capable of accurately interpreting and prioritizing digenic combinations of variants based on the proband's phenotypes and family information can provide valuable assistance during the diagnostic process. We developed diVas, a hypothesis-driven machine learning approach that interprets genomic variants across different gene pairs. DiVas demonstrates strong performance in both classifying and prioritizing causative digenic combinations of rare variants within the top positions across 11 cases with the complete list of variants available (73% sensitivity and a median ranking of 3). Furthermore, it achieves a sensitivity of 0.81 when applied to 645 published causative digenic combinations. Additionally, diVas leverages explainable artificial intelligence to elucidate the digenic disease mechanism for predicted positive pairs.

Benchmark of computational methods to detect digenism in sequencing data

Digenic inheritance is characterized by the combined alteration of two different genes leading to a disease. It could explain the etiology of many currently undiagnosed rare diseases. With the advent of next-generation sequencing technologies, the identification of digenic inheritance patterns has become more technically feasible, yet still poses significant challenges without any gold standard method. Here, we present a comprehensive overview of the existing methods developed to detect digenic inheritance in sequencing data and provide a classification in cohort-based and individual-based methods. The latter category of methods appeared the most applicable to rare diseases, especially the ones not needing patient phenotypic description as input. We discuss the availability of the different methods, their output and scalability to inform potential users. Focusing on methods to detect digenic inheritance in the case of very rare or heterogeneous diseases, we propose a benchmark using different real-life scenarios involving known digenic and putative neutral pairs of genes. Among these different methods, DiGePred stood out as the one giving the least number of false positives, ARBOCK as giving the greatest number of true positives, and DIEP as having the best balance between both. By synthesizing the state-of-the-art techniques and providing insights into their practical utility, this benchmark serves as a valuable resource for researchers and clinicians in selecting suitable methodologies for detecting digenic inheritance in a wide range of disorders using sequencing data.

Deciphering the digenic architecture of congenital heart disease using trio exome sequencing data

Congenital heart disease (CHD) is the most common congenital anomaly and a leading cause of infant morbidity and mortality. Despite extensive exploration of the monogenic causes of CHD over the last decades, ∼55% of cases still lack a molecular diagnosis. Investigating digenic interactions, the simplest form of oligogenic interactions, using high-throughput sequencing data can elucidate additional genetic factors contributing to the disease. Here, we conducted a comprehensive analysis of digenic interactions in CHD by utilizing a large CHD trio exome sequencing cohort, comprising 3,910 CHD and 3,644 control trios. We extracted pairs of presumably deleterious rare variants observed in CHD-affected and unaffected children but not in a single parent. Burden testing of gene pairs derived from these variant pairs revealed 29 nominally significant gene pairs. These gene pairs showed a significant enrichment for known CHD genes (p < 1.0 × 10-4) and exhibited a shorter average biological distance to known CHD genes than expected by chance (p = 3.0 × 10-4). Utilizing three complementary biological relatedness approaches including network analyses, biological distance calculations, and candidate gene prioritization methods, we prioritized 10 final gene pairs that are likely to underlie CHD. Analysis of bulk RNA-sequencing data showed that these genes are highly expressed in the developing embryonic heart (p < 1 × 10-4). In conclusion, our findings suggest the potential role of digenic interactions in CHD pathogenesis and provide insights into unresolved molecular diagnoses. We suggest that the application of the digenic approach to additional disease cohorts will significantly enhance genetic discovery rates.

Digenic Inheritance of PROC and SERPINC1 Mutations Contributes to Multiple Sites Venous Thrombosis

Venous thromboembolism (VTE) represents a worldwide health challenge, impacting millions of people each year. The genesis of venous thrombosis is influenced in part by genetic components. Hereditary thrombosis is described as a genetically determined susceptibility to VTE. In the present study, a male patient was referred to our department presenting with multiple venous thrombosis events in different locations. Given a lack of identifiable risk factors, we aimed to investigate the possible genetic factor underlying venous thrombosis. Whole-exome sequencing was employed to examine genes linked to inherited thrombophilia in the proband. Putative variants were subsequently confirmed through Sanger sequencing within the family. The proband was identified as carrying two genetic mutations. One is the novel c.400G > C (p.E134Q) mutation affecting the final nucleotide of exon 5 in the PROC gene, potentially impacting splicing. The other is a previously reported heterozygous nonsense variant c.1016G > A (p.W339X) in the SERPINC1 gene. The proband inherited the former from her mother and the latter from her father. The presence of digenic inheritance in the patient reflects the complex phenotype of venous thrombosis and demonstrates the significance of an unbiased approach to detect pathogenic variants, especially in patients with a high risk of hereditary thrombosis.

The co-occurrence of genetic variants in the TYR and OCA2 genes confers susceptibility to albinism

Although rare genetic conditions are mostly caused by DNA sequence alterations that functionally disrupt individual genes, large-scale studies using genome sequencing have started to unmask additional complexity. Understanding how combinations of variants in different genes shape human phenotypes is expected to provide important insights into the clinical and genetic heterogeneity of rare disorders. Here, we use albinism, an archetypal rare condition associated with hypopigmentation, as an exemplar for the study of genetic interactions. We analyse data from the Genomics England 100,000 Genomes Project alongside a cohort of 1120 individuals with albinism, and investigate the effect of dual heterozygosity for the combination of two established albinism-related variants: TYR:c.1205 G > A (p.Arg402Gln) [rs1126809] and OCA2:c.1327 G > A (p.Val443Ile) [rs74653330]. As each of these changes alone is insufficient to cause disease when present in the heterozygous state, we sought evidence of synergistic effects. We show that, when both variants are present, the probability of receiving a diagnosis of albinism is significantly increased (odds ratio 12.8; 95% confidence interval 6.0 - 24.7; p-value 2.1 ×10-8). Further analyses in an independent cohort, the UK Biobank, support this finding and highlight that heterozygosity for the TYR:c.1205 G > A and OCA2:c.1327 G > A variant combination is associated with statistically significant alterations in visual acuity and central retinal thickness (traits that are considered albinism endophenotypes). The approach discussed in this report opens up new avenues for the investigation of oligogenic patterns in apparently Mendelian disorders.

Rare heterozygous variants in paediatric steroid resistant nephrotic syndrome - a population-based analysis of their significance

Genetic testing in nephrotic syndrome may identify heterozygous predicted-pathogenic variants (HPPVs) in autosomal recessive (AR) genes that are known to cause disease in the homozygous or compound heterozygous state. In such cases, it can be difficult to define the variant's true significance and questions remain about whether a second pathogenic variant has been missed during analysis or whether the variant is an incidental finding. There are now known to be over 70 genes associated with nephrotic syndrome, the majority inherited as an AR trait. Knowledge of whether such HPPVs occur with equal frequency in patients compared to the general population would assist interpretation of their significance. Exome sequencing was performed on 187 Steroid-Resistant Nephrotic Syndrome (SRNS) paediatric patients recruited to a UK rare disease registry plus originating from clinics at Evelina, London. 59 AR podocytopathy linked genes were analysed in each patient and a list of HPPVs created. We compared the frequency of detected HPPVs with a 'control' population from the gnomAD database containing exome data from approximately 50,000 individuals. A bespoke filtering process was used for both patients and controls to predict 'likely pathogenicity' of variants. In total 130 Caucasian SRNS patients were screened across 59 AR genes and 201 rare heterozygous variants were identified. 17/201 (8.5%) were assigned as 'likely pathogenic' (HPPV) using our bespoke filtering method. Comparing each gene in turn, for SRNS patients with a confirmed genetic diagnosis, in 57 of the 59 genes we found no statistically significant difference in the frequency of these HPPVs between patients and controls (In genes ARHGDIA and TP53RK, we identified a significantly higher number of HPPVs in the control population compared with the patients when filtering was performed with 'high stringency' settings only). In the SRNS patients without a genetics diagnosis confirmed, there was no statistically significant difference identified in any gene between patient and control. In children with SRNS, we propose that identification of HPPV in AR podocytopathy linked genes is not necessarily representative of pathogenicity, given that the frequency is similar to that seen in controls for the majority. Whilst this may not exclude the presence of genetic kidney disease, this type of heterozygous variant is unlikely to be causal and each result must be interpreted in its clinical context.

Prevalence of pathogenic variants and digenic disease in patients diagnosed with normosmic hypogonadotropic hypogonadism/Kallmann Syndrome

BACKGROUND

Hypogonadotropic hypogonadism (HH) is due to impaired gonadotropin releasing hormone (GnRH) action resulting in absent puberty and infertility. At least 44 genes have been identified to possess genetic variants in 40-50% of nHH/KS, and 2-20% have presumed digenic disease, but not all variants have been characterized in vitro.

HYPOTHESIS

The prevalence of pathogenic (P)/likely pathogenic (LP) variants in monogenic and digenic nHH/KS is lower than reported.

DESIGN

Cross-sectional study.

SETTING

University Research Laboratory.

SUBJECTS

158 patients with nHH/KS.

METHODS

Exome sequencing (ES) was performed and variants were filtered for 44 known genes using Varsome and confirmed by Sanger Sequencing.

MAIN OUTCOME MEASURES

P/LP variants in nHH/KS genes.

RESULTS

ES resulted in >370,000 variants, from which variants in 44 genes were filtered. Thirty-one confirmed P/LP variants in 10 genes (ANOS1, CHD7, DUSP6, FGFR1, HS6ST1, KISS1, PROKR2, SEMA3A, SEMA3E, TACR3), sufficient to cause disease, were identified in 30/158 (19%) patients. Only 2/158 (1.2%) patients had digenic variant combinations: a male with hemizygous ANOS1 and heterozygous TACR3 variants and a male with heterozygous SEMA3A and SEMA3E variants. Two patients (1.2%) had compound heterozygous GNRHR (autosomal recessive) variants-one P and one variant of uncertain significance (VUS). Five patients (3.2%) had heterozygous P/LP variants in either GNRHR or TACR3 (both autosomal recessive), but no second variant.

CONCLUSION

Our prevalence of P/LP variants in nHH/KS was 19%, and digenicity was observed in 1.2%. These findings are less than those previously reported, and probably represent a more accurate estimation since VUS are not included.

A pilot study of childhood-onset Takayasu arteritis using whole exome sequencing suggests oligogenic inheritance involving classical complement, collagen, and autoinflammatory pathways

Takayasu arteritis (TA) is a chronic granulomatous inflammatory disease affecting the aorta and its branches. Paediatric TA (pTA) may present from 6 months after birth till the adolescent age group. Genetics and pathogenesis of pTA are not fully understood. Earlier studies reported monogenic mutation in NOD2, XIAP, and STAT1 genes in patients with pTA. TA, a relatively rare disease, is more common in geographical pockets, including India. We hypothesized that South Asian patients with pTA, namely, those of Indian subcontinent origin, may have clinically relevant and unique pathogenic variants involving one or more genes, especially those linked to genetically driven vasculitic illnesses, including autoinflammatory pathologies. Children with pTA fulfilling EULAR/PRINTO/PReS classification criteria and presenting with clinical symptoms to the Paediatric Rheumatology clinic of Christian Medical College, Vellore, were included. Blood samples were collected after getting informed consent from parents or guardians and assent forms from children. DNA was extracted from whole blood using the Qiagen DNA extraction kit. Initially, the common variant in Indian population, namely, ADA2 c.139G > A; p.Gly47Arg, was screened, followed by whole exome sequencing. Fourteen children were recruited for the study. Median age of patients was 11 years (4 months-14 years) with a male-to-female ratio of 4:10. Distribution of angiographic subsets by Numano's classification of included children were as follows: type 5 (n = 7), type 4 (n = 5), and type 3 (n = 2). We identified novel variants in ten different genes. This include variants in genes of classical complement pathway, namely, C2, C3, C6, C7, and C9, and other genes, namely, CYBA, SH3BP2, GUCY2C, CTC1, COL5A1, and NLPR3. Two of 14 patients have heterozygous pathogenic variants; this implies that combination of heterozygous variants in C3 and COL5A1 might lead to disease development, suggesting digenic inheritance. One patient has a homozygous variant in CYBA. None of the patients were identified to have ADA2 variants. Whole exome sequencing reveals combination of rare variants in genes C3, COL5A1, and CYBA associated with disease development in children with Takayasu Arteritis. Key Points • We identified novel variants in genes of classical complement pathway, namely, C2, C3, C6, C7, and C9, and other genes, namely, CYBA, SH3BP2, GUCY2C, CTC1, COL5A1, and NLPR3. • Two of 14 patients have heterozygous pathogenic variants in C3 and COL5A1; this may have implications in disease development, suggesting digenic inheritance. • One patient has homozygous variant in CYBA. • None of the patients were identified to have ADA2 variants.

Exploring the Genotype-Phenotype Correlations in a Child with Inherited Seizure and Thrombocytopenia by Digenic Network Analysis

Understanding the correlation between genotype and phenotype remains challenging for modern genetics. Digenic network analysis may provide useful models for understanding complex phenotypes that traditional Mendelian monogenic models cannot explain. Clinical data, whole exome sequencing data, in silico, and machine learning analysis were combined to construct a digenic network that may help unveil the complex genotype-phenotype correlations in a child presenting with inherited seizures and thrombocytopenia. The proband inherited a maternal heterozygous missense variant in SCN1A (NM_001165963.4:c.2722G>A) and a paternal heterozygous missense variant in MYH9 (NM_002473.6:c.3323A>C). In silico analysis showed that these two variants may be pathogenic for inherited seizures and thrombocytopenia in the proband. Moreover, focusing on 230 epilepsy-associated genes and 35 thrombopoiesis genes, variant call format data of the proband were analyzed using machine learning tools (VarCoPP 2.0) and Digenic Effect predictor. A digenic network was constructed, and SCN1A and MYH9 were found to be core genes in the network. Further analysis showed that MYH9 might be a modifier of SCN1A, and the variant in MYH9 might not only influence the severity of SCN1A-related seizure but also lead to thrombocytopenia in the bone marrow. In addition, another eight variants might also be co-factors that account for the proband's complex phenotypes. Our data show that as a supplement to the traditional Mendelian monogenic model, digenic network analysis may provide reasonable models for the explanation of complex genotype-phenotype correlations.

Clinical and genetic spectrum of RNF216-related disorder: a new case and literature review

BACKGROUND

Cases of RNF216-related disorder have been reported sporadically. However, the clinical and genetic spectrum of this disorder has not been fully studied.

METHODS

We identified an individual with a novel causative RNF216 variant in our institution and reviewed all individuals with causative RNF216 variants in previous reports. The clinical and genetic features of all the described individuals were analysed and summarised.

RESULTS

Twenty-four individuals from 17 families with causative RNF216 variants were identified. The mean age at the onset of neurological symptoms was 29.2 years (range 18-49 years). Ataxia (57%) was the most frequent initial symptoms in individuals under 30 years old, while chorea (63%) was the most frequent initial symptom in individuals over 30 years old. Over 90% of individuals presented with cognitive impairment and hypogonadotropic hypogonadism throughout the disease. White matter lesions (96%) and cerebellar atrophy (92%) were the most common imaging findings. Twenty pathogenic variants in RNF216 were detected. The variants in 12 (71%) families were inherited in a monogenic recessive pattern, whereas the variants in 5 (29%) were inherited in a digenic pattern by acting with variants in other genes. The majority of the RNF216 variants (85%) resulted in amino acid changes or the truncation of the 'RING between RING' (RBR) domain or C-terminal extension.

CONCLUSION

RNF216-related disorder is an inherited neuroendocrine disease characterised by cerebellar ataxia, chorea, cognitive impairment and hypogonadotropic hypogonadism. Most causative variants in patients with RNF216-related disorder influence the RBR domain or C-terminal extension of RNF216.

Digenic inheritance accounts for phenotypic variability in amelogenesis imperfecta

Amelogenesis imperfecta (AI) represents a group of clinically and genetically heterogeneous disorders that affect enamel formation and mineralization. Although AI is commonly considered a monogenic disorder, digenic inheritance is rarely reported. In this study, we recruited two nonconsanguineous Chinese families exhibiting diverse phenotypes of enamel defects among affected family members. Digenic variants were discovered in both probands. In family 1, the proband inherited a paternal frameshift variant in LAMA3 (NM_198129.4:c.3712dup) and a maternal deletion encompassing the entire AMELX gene. This resulted in a combined hypoplastic and hypomineralized AI phenotype, which was distinct from the parents' manifestations. In family 2, whole-exome sequencing analysis revealed the proband carried a maternal heterozygous splicing variant in COL17A1 (NC_000010.11 (NM_000494.3): c.4156 + 2dup) and compound heterozygous variants in RELT (paternal: NM_032871.4:c.260A > T; maternal: NM_032871.4:c.521 T > G). These genetic changes caused the abundant irregular enamel defects observed in the proband, whereas other affected family members carrying heterozygous variants in both COL17A1 and RELT displayed only horizontal grooves as their phenotype. The pathogenicity of the novel COL17A1 splice site variant was confirmed through RT-PCR and minigene assay. This study enhances our understanding by highlighting the potential association between the co-occurrence of variants in two genes and variable phenotypes observed in AI patients.

A knowledge graph approach to predict and interpret disease-causing gene interactions

BACKGROUND

Understanding the impact of gene interactions on disease phenotypes is increasingly recognised as a crucial aspect of genetic disease research. This trend is reflected by the growing amount of clinical research on oligogenic diseases, where disease manifestations are influenced by combinations of variants on a few specific genes. Although statistical machine-learning methods have been developed to identify relevant genetic variant or gene combinations associated with oligogenic diseases, they rely on abstract features and black-box models, posing challenges to interpretability for medical experts and impeding their ability to comprehend and validate predictions. In this work, we present a novel, interpretable predictive approach based on a knowledge graph that not only provides accurate predictions of disease-causing gene interactions but also offers explanations for these results.

RESULTS

We introduce BOCK, a knowledge graph constructed to explore disease-causing genetic interactions, integrating curated information on oligogenic diseases from clinical cases with relevant biomedical networks and ontologies. Using this graph, we developed a novel predictive framework based on heterogenous paths connecting gene pairs. This method trains an interpretable decision set model that not only accurately predicts pathogenic gene interactions, but also unveils the patterns associated with these diseases. A unique aspect of our approach is its ability to offer, along with each positive prediction, explanations in the form of subgraphs, revealing the specific entities and relationships that led to each pathogenic prediction.

CONCLUSION

Our method, built with interpretability in mind, leverages heterogenous path information in knowledge graphs to predict pathogenic gene interactions and generate meaningful explanations. This not only broadens our understanding of the molecular mechanisms underlying oligogenic diseases, but also presents a novel application of knowledge graphs in creating more transparent and insightful predictors for genetic research.

Genetic Modifiers of Mendelian Monogenic Collagen IV Nephropathies in Humans and Mice

Familial hematuria is a clinical sign of a genetically heterogeneous group of conditions, accompanied by broad inter- and intrafamilial variable expressivity. The most frequent condition is caused by pathogenic (or likely pathogenic) variants in the collagen-IV genes, COL4A3/A4/A5. Pathogenic variants in COL4A5 are responsible for the severe X-linked glomerulopathy, Alport syndrome (AS), while homozygous or compound heterozygous variants in the COL4A3 or the COL4A4 gene cause autosomal recessive AS. AS usually leads to progressive kidney failure before the age of 40-years when left untreated. People who inherit heterozygous COL4A3/A4 variants are at-risk of a slowly progressive form of the disease, starting with microscopic hematuria in early childhood, developing Alport spectrum nephropathy. Sometimes, they are diagnosed with benign familial hematuria, and sometimes with autosomal dominant AS. At diagnosis, they often show thin basement membrane nephropathy, reflecting the uniform thin glomerular basement membrane lesion, inherited as an autosomal dominant condition. On a long follow-up, most patients will retain normal or mildly affected kidney function, while a substantial proportion will develop chronic kidney disease (CKD), even kidney failure at an average age of 55-years. A question that remains unanswered is how to distinguish those patients with AS or with heterozygous COL4A3/A4 variants who will manifest a more aggressive kidney function decline, requiring prompt medical intervention. The hypothesis that a subgroup of patients coinherit additional genetic modifiers that exacerbate their clinical course has been investigated by several researchers. Here, we review all publications that describe the potential role of candidate genetic modifiers in patients and include a summary of studies in AS mouse models.

A multi-threaded approach to genotype pattern mining for detecting digenic disease genes

To locate disease-causing DNA variants on the human gene map, the customary approach has been to carry out a genome-wide association study for one variant after another by testing for genotype frequency differences between individuals affected and unaffected with disease. So-called digenic traits are due to the combined effects of two variants, often on different chromosomes, while individual variants may have little or no effect on disease. Machine learning approaches have been developed to find variant pairs underlying digenic traits. However, many of these methods have large memory requirements so that only small datasets can be analyzed. The increasing availability of desktop computers with large numbers of processors and suitable programming to distribute the workload evenly over all processors in a machine make a new and relatively straightforward approach possible, that is, to evaluate all existing variant and genotype pairs for disease association. We present a prototype of such a method with two components, Vpairs and Gpairs, and demonstrate its advantages over existing implementations of such well-known algorithms as Apriori and FP-growth. We apply these methods to published case-control datasets on age-related macular degeneration and Parkinson disease and construct an ROC curve for a large set of genotype patterns.

Phenotypic variability to medication management: an update on fragile X syndrome

This review discusses the discovery, epidemiology, pathophysiology, genetic etiology, molecular diagnosis, and medication-based management of fragile X syndrome (FXS). It also highlights the syndrome's variable expressivity and common comorbid and overlapping conditions. FXS is an X-linked dominant disorder associated with a wide spectrum of clinical features, including but not limited to intellectual disability, autism spectrum disorder, language deficits, macroorchidism, seizures, and anxiety. Its prevalence in the general population is approximately 1 in 5000-7000 men and 1 in 4000-6000 women worldwide. FXS is associated with the fragile X messenger ribonucleoprotein 1 (FMR1) gene located at locus Xq27.3 and encodes the fragile X messenger ribonucleoprotein (FMRP). Most individuals with FXS have an FMR1 allele with > 200 CGG repeats (full mutation) and hypermethylation of the CpG island proximal to the repeats, which silences the gene's promoter. Some individuals have mosaicism in the size of the CGG repeats or in hypermethylation of the CpG island, both produce some FMRP and give rise to milder cognitive and behavioral deficits than in non-mosaic individuals with FXS. As in several monogenic disorders, modifier genes influence the penetrance of FMR1 mutations and FXS's variable expressivity by regulating the pathophysiological mechanisms related to the syndrome's behavioral features. Although there is no cure for FXS, prenatal molecular diagnostic testing is recommended to facilitate early diagnosis. Pharmacologic agents can reduce some behavioral features of FXS, and researchers are investigating whether gene editing can be used to demethylate the FMR1 promoter region to improve patient outcomes. Moreover, clustered regularly interspaced palindromic repeats (CRISPR)/Cas9 and developed nuclease defective Cas9 (dCas9) strategies have promised options of genome editing in gain-of-function mutations to rewrite new genetic information into a specified DNA site, are also being studied.

A systematic review on machine learning approaches in the diagnosis and prognosis of rare genetic diseases

BACKGROUND

The diagnosis of rare genetic diseases is often challenging due to the complexity of the genetic underpinnings of these conditions and the limited availability of diagnostic tools. Machine learning (ML) algorithms have the potential to improve the accuracy and speed of diagnosis by analyzing large amounts of genomic data and identifying complex multiallelic patterns that may be associated with specific diseases. In this systematic review, we aimed to identify the methodological trends and the ML application areas in rare genetic diseases.

METHODS

We performed a systematic review of the literature following the PRISMA guidelines to search studies that used ML approaches to enhance the diagnosis of rare genetic diseases. Studies that used DNA-based sequencing data and a variety of ML algorithms were included, summarized, and analyzed using bibliometric methods, visualization tools, and a feature co-occurrence analysis.

FINDINGS

Our search identified 22 studies that met the inclusion criteria. We found that exome sequencing was the most frequently used sequencing technology (59%), and rare neoplastic diseases were the most prevalent disease scenario (59%). In rare neoplasms, the most frequent applications of ML models were the differential diagnosis or stratification of patients (38.5%) and the identification of somatic mutations (30.8%). In other rare diseases, the most frequent goals were the prioritization of rare variants or genes (55.5%) and the identification of biallelic or digenic inheritance (33.3%). The most employed method was the random forest algorithm (54.5%). In addition, the features of the datasets needed for training these algorithms were distinctive depending on the goal pursued, including the mutational load in each gene for the differential diagnosis of patients, or the combination of genotype features and sequence-derived features (such as GC-content) for the identification of somatic mutations.

CONCLUSIONS

ML algorithms based on sequencing data are mainly used for the diagnosis of rare neoplastic diseases, with random forest being the most common approach. We identified key features in the datasets used for training these ML models according to the objective pursued. These features can support the development of future ML models in the diagnosis of rare genetic diseases.

Clinical and Functional Assessment of Digenicity in Renal Phosphate Wasting

Apart from increased fluid intake, patients with kidney stone disease (KSD) due to renal phosphate wasting require specific metaphylaxis. NaPi2a, NaPi2c, and NHERF1 regulate plasma phosphate concentration by reabsorbing phosphate in proximal kidney tubules and have been found altered in monogenic hypophosphatemia with a risk of KSD. In this study, we aimed at assessing the combined genetic alterations impacting NaPi2a, NaPi2c, and NHERF1. Therefore, we screened our hereditary KSD registry for cases of oligo- and digenicity, conducted reverse phenotyping, and undertook functional studies. As a result, we identified three patients from two families with digenic alterations in NaPi2a, NaPi2c, and NHERF1. In family 1, the index patient, who presented with severe renal calcifications and a bone mineralization disorder, carried digenic alterations affecting both NaPi transporter 2a and 2c. Functional analysis confirmed an additive genetic effect. In family 2, the index patient presented with kidney function decline, distinct musculature-related symptoms, and intracellular ATP depletion. Genetically, this individual was found to harbor variants in both NaPi2c and NHERF1 pointing towards genetic interaction. In summary, digenicity and gene dosage are likely to impact the severity of renal phosphate wasting and should be taken into account in terms of metaphylaxis through phosphate substitution.

Nuclear Receptor Gene Variants Underlying Disorders/Differences of Sex Development through Abnormal Testicular Development

Gonadal development is the first step in human reproduction. Aberrant gonadal development during the fetal period is a major cause of disorders/differences of sex development (DSD). To date, pathogenic variants of three nuclear receptor genes (NR5A1, NR0B1, and NR2F2) have been reported to cause DSD via atypical testicular development. In this review article, we describe the clinical significance of the NR5A1 variants as the cause of DSD and introduce novel findings from recent studies. NR5A1 variants are associated with 46,XY DSD and 46,XX testicular/ovotesticular DSD. Notably, both 46,XX DSD and 46,XY DSD caused by the NR5A1 variants show remarkable phenotypic variability, to which digenic/oligogenic inheritances potentially contribute. Additionally, we discuss the roles of NR0B1 and NR2F2 in the etiology of DSD. NR0B1 acts as an anti-testicular gene. Duplications containing NR0B1 result in 46,XY DSD, whereas deletions encompassing NR0B1 can underlie 46,XX testicular/ovotesticular DSD. NR2F2 has recently been reported as a causative gene for 46,XX testicular/ovotesticular DSD and possibly for 46,XY DSD, although the role of NR2F2 in gonadal development is unclear. The knowledge about these three nuclear receptors provides novel insights into the molecular networks involved in the gonadal development in human fetuses.

Digenic genotypes: The interface of inbreeding, linkage, and linkage disequilibrium

Many traits in populations are well understood as being Mendelian effects at single loci or additive polygenic effects across numerous loci. However, there are important phenomena and traits that are intermediate between these two extremes and are known as oligogenic traits. Here we investigate digenic, or two-locus, traits and how their frequencies in populations are affected by non-random mating, specifically inbreeding, linkage disequilibrium, and selection. These effects are examined both separately and in combination to demonstrate how many digenic traits, especially double homozygous ones, can show significant, sometimes unexpected, changes in population frequency with inbreeding, linkage, and linkage disequilibrium. The effects of selection on deleterious digenic traits are also detailed. These results are applied to both digenic traits of medical significance as well as measuring inbreeding in natural populations.

Congenital hydrocephalus: new Mendelian mutations and evidence for oligogenic inheritance

BACKGROUND

Congenital hydrocephalus is characterized by ventriculomegaly, defined as a dilatation of cerebral ventricles, and thought to be due to impaired cerebrospinal fluid (CSF) homeostasis. Primary congenital hydrocephalus is a subset of cases with prenatal onset and absence of another primary cause, e.g., brain hemorrhage. Published series report a Mendelian cause in only a minority of cases. In this study, we analyzed exome data of PCH patients in search of novel causal genes and addressed the possibility of an underlying oligogenic mode of inheritance for PCH.

MATERIALS AND METHODS

We sequenced the exome in 28 unrelated probands with PCH, 12 of whom from families with at least two affected siblings and 9 of whom consanguineous, thereby increasing the contribution of genetic causes. Patient exome data were first analyzed for rare (MAF < 0.005) transmitted or de novo variants. Population stratification of unrelated PCH patients and controls was determined by principle component analysis, and outliers identified using Mahalanobis distance 5% as cutoff. Patient and control exome data for genes biologically related to cilia (SYScilia database) were analyzed by mutation burden test.

RESULTS

In 18% of probands, we identify a causal (pathogenic or likely pathogenic) variant of a known hydrocephalus gene, including genes for postnatal, syndromic hydrocephalus, not previously reported in isolated PCH. In a further 11%, we identify mutations in novel candidate genes. Through mutation burden tests, we demonstrate a significant burden of genetic variants in genes coding for proteins of the primary cilium in PCH patients compared to controls.

CONCLUSION

Our study confirms the low contribution of Mendelian mutations in PCH and reports PCH as a phenotypic presentation of some known genes known for syndromic, postnatal hydrocephalus. Furthermore, this study identifies novel Mendelian candidate genes, and provides evidence for oligogenic inheritance implicating primary cilia in PCH.

The emergence of genotypic divergence and future precision medicine applications

Genotypic divergence is a term adapted from population genetics and intimately linked to evolution. We use divergence here to emphasize the differences that set individuals apart in any cohort. The history of genetics is filled with descriptions of genotypic differences, but causal inference of interindividual biological variation has been scarce. We suggest that the practice of precision medicine requires a divergent approach, an approach dependent on the causal interpretation of previous convergent (and preliminary) knowledge in the field. This knowledge has relied on convergent descriptive syndromology (lumping), which has overemphasized a reductionistic gene determinism on the quest of seeking associations without causal understanding. Regulatory variants with small effect and somatic mutations are some of the modifying factors that lead to incomplete penetrance and intrafamilial variable expressivity often observed in apparently monogenic clinical disorders. A truly divergent approach to precision medicine requires splitting, that is, the consideration of different layers of genetic phenomena that interact causally in a nonlinear fashion. This chapter reviews convergences and divergences in genetics and genomics, aiming to discuss what can be causally understood to approximate the as-yet utopian lands of Precision Medicine for patients with neurodegenerative disorders.

Mendelian inheritance revisited: dominance and recessiveness in medical genetics

Understanding the consequences of genotype for phenotype (which ranges from molecule-level effects to whole-organism traits) is at the core of genetic diagnostics in medicine. Many measures of the deleteriousness of individual alleles exist, but these have limitations for predicting the clinical consequences. Various mechanisms can protect the organism from the adverse effects of functional variants, especially when the variant is paired with a wild type allele. Understanding why some alleles are harmful in the heterozygous state - representing dominant inheritance - but others only with the biallelic presence of pathogenic variants - representing recessive inheritance - is particularly important when faced with the deluge of rare genetic alterations identified by high throughput DNA sequencing. Both awareness of the specific quantitative and/or qualitative effects of individual variants and the elucidation of allelic and non-allelic interactions are essential to optimize genetic diagnosis and counselling.

A new enrichment approach for candidate gene detection in unexplained recurrent pregnancy loss and implantation failure

Recurrent pregnancy loss (RPL) and implantation failure (RIF) are obstacles to livebirth and multifactorial conditions in which nearly half of the cases remain unexplained, and we aimed to identify maternal candidate gene variants and pathways for RPL and RIF by analyzing whole-exome sequencing (WES) data via a new detailed bioinformatics approach. A retrospective cohort study was applied to 35 women with normal chromosomal configuration diagnosed with unexplained RPL and/or RIF. WES and comprehensive bioinformatics analyses were performed. Published gene expression datasets (n = 46) were investigated for candidate genes. Variant effects on protein structure were analyzed for 12 proteins, and BUB1B was visualized in silico. WES and bioinformatics analyses are effective and applicable for studying URPL and RIF to detect mutations, as we suggest new candidates to explain the etiology. Forty-three variants in 39 genes were detected in 29 women, 7 of them contributing to oligogenic inheritance. These genes were related to implantation, placentation, coagulation, metabolism, immune system, embryological development, cell cycle-associated processes, and ovarian functions. WES, genomic variant analyses, expression data, and protein configuration studies offer new and promising ways to investigate the etiology of URPL and RIF. Discovering etiology-identifying genetic factors can help manage couples' needs and develop personalized therapies and new pharmaceutical products in the future. The classical approach with chromosomal analysis and targeted gene panel testing is insufficient in these cases; the exome data provide a promising way to detect and understand the possible clinical effects of the variant and its alteration on protein structure.

Toward reporting standards for the pathogenicity of variant combinations involved in multilocus/oligogenic diseases

Although standards and guidelines for the interpretation of variants identified in genes that cause Mendelian disorders have been developed, this is not the case for more complex genetic models including variant combinations in multiple genes. During a large curation process conducted on 318 research articles presenting oligogenic variant combinations, we encountered several recurring issues concerning their proper reporting and pathogenicity assessment. These mainly concern the absence of strong evidence that refutes a monogenic model and the lack of a proper genetic and functional assessment of the joint effect of the involved variants. With the increasing accumulation of such cases, it has become essential to develop standards and guidelines on how these oligogenic/multilocus variant combinations should be interpreted, validated, and reported in order to provide high-quality data and supporting evidence to the scientific community.

Assessing the digenic model in rare disorders using population sequencing data

An important fraction of patients with rare disorders remains with no clear genetic diagnostic, even after whole-exome or whole-genome sequencing, posing a difficulty in giving adequate treatment and genetic counseling. The analysis of genomic data in rare disorders mostly considers the presence of single gene variants in coding regions that follow a concrete monogenic mode of inheritance. A digenic inheritance, with variants in two functionally-related genes in the same individual, is a plausible alternative that might explain the genetic basis of the disease in some cases. In this case, digenic disease combinations should be absent or underrepresented in healthy individuals. We develop a framework to evaluate the significance of digenic combinations and test its statistical power in different scenarios. We suggest that this approach will be relevant with the advent of new sequencing efforts including hundreds of thousands of samples.

Digenic Alport Syndrome

Digenic Alport syndrome refers to the inheritance of pathogenic variants in COL4A5 plus COL4A3 or COL4A4 or in COL4A3 plus COL4A4 Where digenic Alport syndrome includes a pathogenic COL4A5 variant, the consequences depend on the sex of the affected individual, COL4A5 variant "severity," and the nature of the COL4A3 or COL4A4 change. A man with a pathogenic COL4A5 variant has all his collagen IV α3α4α5-heterotrimers affected, and an additional COL4A3 or COL4A4 variant may not worsen disease. A woman with a pathogenic COL4A5 variant has on average 50% of her heterotrimers affected, which is increased to 75% with a further COL4A3 or COL4A4 variant and associated with a higher risk of proteinuria. In digenic Alport syndrome with pathogenic COL4A3 and COL4A4 variants, 75% of the heterotrimers are affected. The COL4A3 and COL4A4 genes occur head-to-head on chromosome 2, and inheritance is autosomal dominant when both variants affect the same chromosome (in cis) or recessive when they affect different chromosomes (in trans). This form of digenic disease results in increased proteinuria and a median age of kidney failure intermediate between autosomal dominant and autosomal recessive Alport syndrome. Previous guidelines have suggested that all pathogenic or likely pathogenic digenic variants should be identified and reported. Affected family members should be identified, treated, and discouraged from kidney donation. Inheritance within a family is easier to predict if the two variants are considered independently and if COL4A3 and COL4A4 variants are known to be inherited on the same or different chromosomes.

An accurate prediction model of digenic interaction for estimating pathogenic gene pairs of human diseases

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Numerous pathogenic interactions are yet to be revealed efficiently due to dimension burden.

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Existing methods are underpowered and inaccurate to estimate pathogenic interactions.

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We developed an accurate bioinformatic method to predict digenic interaction effects based on gene-level features.

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The new method created a valuable resource of genome-wide pathogenic digenic interactions.

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We found that known causal genes in Mendelian and Oligogenic diseases may be enriched with interactive effects for the first time.

Increasing evidence shows that genetic interaction across the entire genome may explain a non-trivial fraction of genetic diseases. Digenic interaction is the simplest manifestation of genetic interaction among genes. However, systematic exploration of digenic interactive effects on the whole genome is often discouraged by the high dimension burden. Thus, numerous digenic interactions are yet to be identified for many diseases. Here, we propose a Digenic Interaction Effect Predictor (DIEP), an accurate machine-learning approach to identify the genome-wide pathogenic coding gene pairs with digenic interaction effects. This approach achieved high accuracy and sensitivity in independent testing datasets, outperforming another gene-level digenic predictor (DiGePred). DIEP was also able to discriminate digenic interaction effect from bi-locus effects dual molecular diagnosis (pseudo-digenic). Using DIEP, we provided a valuable resource of genome-wide digenic interactions and demonstrated the enrichment of the digenic interaction effect in Mendelian and Oligogenic diseases. Therefore, DIEP will play a useful role in facilitating the genomic mapping of interactive causal genes for human diseases.

The Parkinson's disease variant rs356182 regulates neuronal differentiation independently from alpha-synuclein

One of the most significant risk variants for Parkinson's disease (PD), rs356182, is located at the PD-associated locus near the alpha-synuclein (α-syn) encoding gene, SNCA. SNCA-proximal variants, including rs356182, are thought to function in PD risk through enhancers via allele-specific regulatory effects on SNCA expression. However, this interpretation discounts the complex activity of genetic enhancers and possible non-conical functions of α-syn. Here we investigated a novel risk mechanism for rs356182. We use CRISPR-Cas9 in LUHMES cells, a model for dopaminergic midbrain neurons, to generate precise hemizygous lesions at rs356182. The PD-protective (A/-), PD-risk (G/-) and wild-type (A/G) clones were neuronally differentiated and then compared transcriptionally and morphologically. Among the affected genes was SNCA, whose expression was promoted by the PD-protective allele (A) and repressed in its absence. In addition to SNCA, hundreds of genes were differentially expressed and associated with neurogenesis and axonogenesis-an effect not typically ascribed to α-syn. We also found that the transcription factor FOXO3 specifically binds to the rs356182 A-allele in differentiated LUHMES cells. Finally, we compared the results from the rs356182-edited cells to our previously published knockouts of SNCA and found only minimal overlap between the sets of significant differentially expressed genes. Together, the data implicate a risk mechanism for rs356182 in which the risk-allele (G) is associated with abnormal neuron development, independent of SNCA expression. We speculate that these pathological effects manifest as a diminished population of dopaminergic neurons during development leading to the predisposition for PD later in life.

Exome Sequencing Identifies the Extremely Rare ITGAV and FN1 Variants in Early Onset Inflammatory Bowel Disease Patients

Background

Molecular diagnosis of early onset inflammatory bowel disease (IBD) is very important for adopting suitable treatment strategies. Owing to the sparse data available, this study aims to identify the molecular basis of early onset IBD in Arab patients.

Methods

A consanguineous Arab family with monozygotic twins presenting early onset IBD was screened by whole exome sequencing (WES). The variants functional characterization was performed by a series of computational biology methods. The IBD variants were further screened in in-house whole exome data of 100 Saudi cohorts ensure their rare prevalence in the population.

Results

Genetic screening has identified the digenic autosomal recessive mode of inheritance of ITGAV (G58V) and FN1 (G313V) variants in IBD twins with early onset IBD. Findings from pathogenicity predictions, stability and molecular dynamics have confirmed the deleterious nature of both variants on structural features of the corresponding proteins. Functional biology data suggested that both genes show abundant expression in gastrointestinal tract and immune organs, involved in immune cell restriction, regulation of different immune related pathways. Data from knockout mouse models for ITGAV gene has revealed that the dysregulated expression of this gene impacts intestinal immune homeostasis. The defective ITGAV and FN1 involved in integrin pathway, are likely to induce intestinal inflammation by disturbing immune homeostasis.

Conclusions

Our findings provide novel insights into the molecular etiology of pediatric onset IBD and may likely pave way in developing genomic medicine.

Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database

Improving the understanding of the oligogenic nature of diseases requires access to high-quality, well-curated Findable, Accessible, Interoperable, Reusable (FAIR) data. Although first steps were taken with the development of the Digenic Diseases Database, leading to novel computational advancements to assist the field, these were also linked with a number of limitations, for instance, the ad hoc curation protocol and the inclusion of only digenic cases. The OLIgogenic diseases DAtabase (OLIDA) presents a novel, transparent and rigorous curation protocol, introducing a confidence scoring mechanism for the published oligogenic literature. The application of this protocol on the oligogenic literature generated a new repository containing 916 oligogenic variant combinations linked to 159 distinct diseases. Information extracted from the scientific literature is supplemented with current knowledge support obtained from public databases. Each entry is an oligogenic combination linked to a disease, labelled with a confidence score based on the level of genetic and functional evidence that supports its involvement in this disease. These scores allow users to assess the relevance and proof of pathogenicity of each oligogenic combination in the database, constituting markers for reporting improvements on disease-causing oligogenic variant combinations. OLIDA follows the FAIR principles, providing detailed documentation, easy data access through its application programming interface and website, use of unique identifiers and links to existing ontologies.

Identification of Novel Mutations in Chinese Infants With Citrullinemia

Citrullinemia is a rare autosomal recessive disorder characterized by elevated concentrations of citrulline in the blood resulting from malfunction of the urea cycle. It is categorized into two types, types I and II, which are caused by argininosuccinate synthase 1 (ASS1), and citrin (SLC25A13) gene mutations, respectively. In this study, we performed genetic analysis on nine Chinese infants with citrullinemia using next-generation sequencing, which identified a novel mutation (p.Leu313Met) and a rare mutation (p.Thr323Ile, rs1250895424) of ASS1. We also found a novel splicing mutation of SLC25A13: c.1311 + 4_+7del. Functional analysis of the ASS1 missense mutations showed that both significantly impaired the enzyme activity of ASS1, with the p. Thr323Ile mutation clearly affecting the interaction between ASS1 and protein arginine methyltransferase 7 (PRMT7). These findings expand the mutational spectrum of ASS1 and SLC25A13, and further our understanding of the molecular genetic mechanism of citrullinemia in the Chinese population.

Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy

Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology. Additionally, we discuss the strategy, challenge, and promise of gene therapy. As computational and statistical approaches continue to improve, we will have an opportunity to translate human genetic findings into personalized health care.

Digenic Inheritance: Evidence and Gaps in Hemophagocytic Lymphohistiocytosis

Hemophagocytic lymphohistiocytosis (HLH) is a hyperinflammatory disorder characterized by the inability to properly terminate an immune response. Familial HLH (FHLH) and related immune dysregulation syndromes are associated with mutations in the genes PRF1, UNC13D, STX11, STXBP2, LYST, AP3B1, and RAB27A, all of which are required for the assembly, exocytosis, and function of cytotoxic granules within CD8+ T cells and natural killer (NK) cells. Loss-of-function mutations in these genes render the cytotoxicity pathway ineffective, thereby failing to eradicate immune stimuli, such as infectious pathogens or malignant cells. The resulting persistent immune system stimulation drives hypercytokinemia, ultimately leading to severe tissue inflammation and end-organ damage. Traditionally, a diagnosis of FHLH requires the identification of biallelic loss-of-function mutations in one of these degranulation pathway genes. However, this narrow definition fails to encompass patients with other genetic mechanisms underlying degranulation pathway dysfunction. In particular, mounting clinical evidence supports a potential digenic mode of inheritance of FHLH in which single loss-of-function mutations in two different degranulation pathway genes cooperate to impair pathway activity. Here, we review the functions of the FHLH-associated genes within the degranulation pathway and summarize clinical evidence supporting a model in which cumulative defects along this mechanistic pathway may underlie HLH.

Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network

Rare diseases affect millions of people worldwide, and discovering their genetic causes is challenging. More than half of the individuals analyzed by the Undiagnosed Diseases Network (UDN) remain undiagnosed. The central hypothesis of this work is that many of these rare genetic disorders are caused by multiple variants in more than one gene. However, given the large number of variants in each individual genome, experimentally evaluating combinations of variants for potential to cause disease is currently infeasible. To address this challenge, we developed the digenic predictor (DiGePred), a random forest classifier for identifying candidate digenic disease gene pairs by features derived from biological networks, genomics, evolutionary history, and functional annotations. We trained the DiGePred classifier by using DIDA, the largest available database of known digenic-disease-causing gene pairs, and several sets of non-digenic gene pairs, including variant pairs derived from unaffected relatives of UDN individuals. DiGePred achieved high precision and recall in cross-validation and on a held-out test set (PR area under the curve > 77%), and we further demonstrate its utility by using digenic pairs from the recent literature. In contrast to other approaches, DiGePred also appropriately controls the number of false positives when applied in realistic clinical settings. Finally, to enable the rapid screening of variant gene pairs for digenic disease potential, we freely provide the predictions of DiGePred on all human gene pairs. Our work enables the discovery of genetic causes for rare non-monogenic diseases by providing a means to rapidly evaluate variant gene pairs for the potential to cause digenic disease.

PDigenic Mutations in Junctional Epidermolysis Bullosa in An Iranian Family

In this study, we describe one Iranian patient who was diagnosed with Epidermolysis Bullosa (EB) because of mutations in three candidate genes, including 3 mutations. Two missense mutations in the LAMA3 (D3134H) and LAMB3 (Y339H) genes and also, a synonymous mutation in the ITGB4 (H422H) gene were identified that leads to the Junctional-EB- Herlitz (JEB-Herlitz) clinical phenotype. The patient had a heterozygous LAMA3 mutation combined with a heterozygous mutation in LAMB3. Our results propose that these mutations produce novel protein-coding transcripts which explain the JEB-Herlitz phenotype in the patient. Interestingly, this is the first report indicating that a digenic inheritance in the LAMA3 and LAMB3 which is responsible for JEB-Herlitz. Also, this is the first digenic inheritance recognized in the JEB-Herlitz family. This study provides a new way to clarify the molecular mechanisms of LAMA3 and LAMB3 genes in JEB-Herlitz.

Genetics of hypogonadotropic Hypogonadism-Human and mouse genes, inheritance, oligogenicity, and genetic counseling

Hypogonadotropic hypogonadism, which may be normosmic (nHH) or anosmic/hyposmic, known as Kallmann syndrome (KS), is due to gonadotropin-releasing hormone deficiency, which results in absent puberty and infertility. Investigation of the genetic basis of nHH/KS over the past 35 years has yielded a substantial increase in our understanding, as variants in 44 genes in OMIM account for ~50% of cases. The first genes for KS (ANOS1) and nHH (GNRHR) were followed by the discovery that FGFR1 variants may cause either nHH or KS. Associated anomalies include midline facial defects, neurologic deficits, cardiac anomalies, and renal agenesis, among others. Mouse models for all but one gene (ANOS1) generally support findings in humans. About half of the known genes implicated in nHH/KS are inherited as autosomal dominant and half are autosomal recessive, whereas only 7% are X-linked recessive. Digenic and oligogenic inheritance has been reported in 2-20% of patients, most commonly with variants in genes that may result in either nHH or KS inherited in an autosomal dominant fashion. In vitro analyses have only been conducted for both gene variants in eight cases and for one gene variant in 20 cases. Rigorous confirmation that two gene variants in the same individual cause the nHH/KS phenotype is lacking for most. Clinical diagnosis is probably best accomplished by targeted next generation sequencing of the known candidate genes with confirmation by Sanger sequencing. Elucidation of the genetic basis of nHH/KS has resulted in an enhanced understanding of this disorder, as well as normal puberty, which makes genetic diagnosis clinically relevant.

Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits

Some genetic diseases ("digenic traits") are due to the interaction between two DNA variants, which presumably reflects biochemical interactions. For example, certain forms of Retinitis Pigmentosa, a type of blindness, occur in the presence of two mutant variants, one each in the ROM1 and RDS genes, while the occurrence of only one such variant results in a normal phenotype. Detecting variant pairs underlying digenic traits by standard genetic methods is difficult and is downright impossible when individual variants alone have minimal effects. Frequent pattern mining (FPM) methods are known to detect patterns of items. We make use of FPM approaches to find pairs of genotypes (from different variants) that can discriminate between cases and controls. Our method is based on genotype patterns of length two, and permutation testing allows assigning p-values to genotype patterns, where the null hypothesis refers to equal pattern frequencies in cases and controls. We compare different interaction search approaches and their properties on the basis of published datasets. Our implementation of FPM to case-control studies is freely available.

Variable Expressivity in Fragile X Syndrome: Towards the Identification of Molecular Characteristics That Modify the Phenotype

Fragile X syndrome (FXS), is an X-linked inherited genetic disease. FXS is the leading cause of inherited intellectual disability and autism in the world. Those affected are characterized by intellectual disability, language deficit, typical facies, and macroorchidism. Alterations in the FMR1 gene have been associated with FXS. The majority of people with this condition have an allele with an expansion of more than 200 repeats in a tract of CGGs within the 5' untranslated region, and this expansion is associated with a hypermethylated state of the gene promoter. FXS has incomplete penetrance and variable expressivity. Intellectual disability is present in 100% of males and 60% of females. Autism spectrum disorder symptoms appear in 50% to 60% of males and 20% of females. Other characteristics such as behavioral and physical alterations have significant variations in presentation frequency. The molecular causes of the variable phenotype in FXS patients are becoming clear: these causes are related to the FMR1 gene itself and to secondary, modifying gene effects. In FXS patients, size and methylation mosaicisms are common. Secondary to mosaicism, there is a variation in the quantity of FMR1 mRNA and the protein coded by the gene Fragile Mental Retardation Protein (FMRP). Potential modifier genes have also been proposed, with conflicting results. Characterizing patients according to CGG expansion, methylation status, concentration of mRNA and FMRP, and genotypification for possible modifier genes in a clinical setting offers an opportunity to identify predictors for treatment response evaluation. When intervention strategies become available to modulate the course of the disease they could be crucial for selecting patients and identifying the best therapeutic intervention. The purpose of this review is to present the information available about the molecular causes of the variability of the expression incomplete penetrance and variable expressivity in FXS and their potential clinical applications.

Evidence for Non-Mendelian Inheritance in Spastic Paraplegia 7

BACKGROUND

Although the typical inheritance of spastic paraplegia 7 is recessive, several reports have suggested that SPG7 variants may also cause autosomal dominant hereditary spastic paraplegia (HSP).

OBJECTIVES

We aimed to conduct an exome-wide genetic analysis on a large Canadian cohort of HSP patients and controls to examine the association of SPG7 and HSP.

METHODS

We analyzed 585 HSP patients from 372 families and 1175 controls, including 580 unrelated individuals. Whole-exome sequencing was performed on 400 HSP patients (291 index cases) and all 1175 controls.

RESULTS

The frequency of heterozygous pathogenic/likely pathogenic SPG7 variants (4.8%) among unrelated HSP patients was higher than among unrelated controls (1.7%; OR 2.88, 95% CI 1.24-6.66, P = 0.009). The heterozygous SPG7 p.(Ala510Val) variant was found in 3.7% of index patients versus 0.85% in unrelated controls (OR 4.42, 95% CI 1.49-13.07, P = 0.005). Similar results were obtained after including only genetically-undiagnosed patients. We identified four heterozygous SPG7 variant carriers with an additional pathogenic variant in known HSP genes, compared to zero in controls (OR 19.58, 95% CI 1.05-365.13, P = 0.0031), indicating potential digenic inheritance. We further identified four families with heterozygous variants in SPG7 and SPG7-interacting genes (CACNA1A, AFG3L2, and MORC2). Of these, there is especially compelling evidence for epistasis between SPG7 and AFG3L2. The p.(Ile705Thr) variant in AFG3L2 is located at the interface between hexamer subunits, in a hotspot of mutations associated with spinocerebellar ataxia type 28 that affect its proteolytic function.

CONCLUSIONS

Our results provide evidence for complex inheritance in SPG7-associated HSP, which may include recessive and possibly dominant and digenic/epistasis forms of inheritance. © 2021 International Parkinson and Movement Disorder Society.

The Digenic Causality in Familial Hypercholesterolemia: Revising the Genotype-Phenotype Correlations of the Disease

Genetically inherited defects in lipoprotein metabolism affect more than 10 million individuals around the globe with preponderance in some parts where consanguinity played a major role in establishing founder mutations. Mutations in four genes have been so far linked to the dominant and recessive form of the disease. Those players encode major proteins implicated in cholesterol regulation, namely, the low-density lipoprotein receptor (LDLR) and its associate protein 1 (LDLRAP1), the proprotein convertase substilin/kexin type 9 (PCSK9), and the apolipoprotein B (APOB). Single mutations or compound mutations in one of these genes are enough to account for a spectrum of mild to severe phenotypes. However, recently several reports have identified digenic mutations in familial cases that do not necessarily reflect a much severe phenotype. Yet, data in the literature supporting this notion are still lacking. Herein, we review all the reported cases of digenic mutations focusing on the biological impact of gene dosage and the potential protective effects of single-nucleotide polymorphisms linked to hypolipidemia. We also highlight the difficulty of establishing phenotype-genotype correlations in digenic familial hypercholesterolemia cases due to the complexity and heterogeneity of the phenotypes and the still faulty in silico pathogenicity scoring system. We finally emphasize the importance of having a whole exome/genome sequencing approach for all familial cases of familial hyperlipidemia to better understand the genetic and clinical course of the disease.

The GENDULF algorithm: mining transcriptomics to uncover modifier genes for monogenic diseases

Modifier genes are believed to account for the clinical variability observed in many Mendelian disorders, but their identification remains challenging due to the limited availability of genomics data from large patient cohorts. Here, we present GENDULF (GENetic moDULators identiFication), one of the first methods to facilitate prediction of disease modifiers using healthy and diseased tissue gene expression data. GENDULF is designed for monogenic diseases in which the mechanism is loss of function leading to reduced expression of the mutated gene. When applied to cystic fibrosis, GENDULF successfully identifies multiple, previously established disease modifiers, including EHF, SLC6A14, and CLCA1. It is then utilized in spinal muscular atrophy (SMA) and predicts U2AF1 as a modifier whose low expression correlates with higher SMN2 pre-mRNA exon 7 retention. Indeed, knockdown of U2AF1 in SMA patient-derived cells leads to increased full-length SMN2 transcript and SMN protein expression. Taking advantage of the increasing availability of transcriptomic data, GENDULF is a novel addition to existing strategies for prediction of genetic disease modifiers, providing insights into disease pathogenesis and uncovering novel therapeutic targets.

Digenic mutations in ALDH2 and ADH5 impair formaldehyde clearance and cause a multisystem disorder, AMeD syndrome

Rs671 in the aldehyde dehydrogenase 2 gene (ALDH2) is the cause of Asian alcohol flushing response after drinking. ALDH2 detoxifies endogenous aldehydes, which are the major source of DNA damage repaired by the Fanconi anemia pathway. Here, we show that the rs671 defective allele in combination with mutations in the alcohol dehydrogenase 5 gene, which encodes formaldehyde dehydrogenase (ADH5FDH ), causes a previously unidentified disorder, AMeD (aplastic anemia, mental retardation, and dwarfism) syndrome. Cellular studies revealed that a decrease in the formaldehyde tolerance underlies a loss of differentiation and proliferation capacity of hematopoietic stem cells. Moreover, Adh5-/-Aldh2 E506K/E506K double-deficient mice recapitulated key clinical features of AMeDS, showing short life span, dwarfism, and hematopoietic failure. Collectively, our results suggest that the combined deficiency of formaldehyde clearance mechanisms leads to the complex clinical features due to overload of formaldehyde-induced DNA damage, thereby saturation of DNA repair processes.

Clinical and molecular evidence of possible digenic inheritance for MFN2/GDAP1 genes in Charcot-Marie-Tooth disease

Charcot Marie Tooth disease (CMT) is a progressive motor and sensory polyneuropathy, it is characterized by a very heterogeneous molecular basis and phenotype. MFN2 and GDAP1 participate in mitochondrial energy metabolism and the rare coinheritance of its pathogenic variants has been associated with a cumulative effect in the observed phenotype. We describe a patient with a severe axonal CMT and inherited heterozygous MFN2 (p.Leu741Val) and GDAP1 (p.Gln163*) variants. In accordance with a possible digenic inheritance, none of the heterozygous carriers in his family were symptomatic or exhibited electrophysiological abnormalities. We also review all of the previously reported patients with coinheritance of variants in these two genes; similar to our patient, all exhibit a predominantly axonal severe CMT phenotype. Our findings expand the genotypic spectrum of CMT and further support that digenic inheritance should be considered for analyzing and counseling CMT patients.

Mutational burden and potential oligogenic model of TBX6-mediated genes in congenital scoliosis

BACKGROUND

Congenital scoliosis (CS) is a spinal deformity due to vertebral malformations. Although insufficiency of TBX6 dosage contributes to a substantial proportion of CS, the molecular etiology for the majority of CS remains largely unknown. TBX6-mediated genes involved in the process of somitogenesis represent promising candidates.

METHODS

Individuals affected with CS and without a positive genetic finding were referred to this study. Proband-only exome sequencing (ES) were performed on the recruited individuals, followed by analysis of TBX6-mediated candidate genes, namely MEOX1, MEOX2, MESP2, MYOD1, MYF5, RIPPLY1, and RIPPLY2.

RESULTS

A total of 584 patients with CS of unknown molecular etiology were recruited. After ES analysis, protein-truncating variants in RIPPLY1 and MYF5 were identified from two individuals, respectively. In addition, we identified five deleterious missense variants (MYOD1, n = 4; RIPPLY2, n = 1) in TBX6-mediated genes. We observed a significant mutational burden of MYOD1 in CS (p = 0.032) compared with the in-house controls (n = 1854). Moreover, a potential oligogenic disease-causing mode was proposed based on the observed mutational co-existence of MYOD1/MEOX1 and MYOD1/RIPPLY1.

CONCLUSION

Our study characterized the mutational spectrum of TBX6-mediated genes, prioritized core candidate genes/variants, and provided insight into a potential oligogenic disease-causing mode in CS.

Further evidence for the association of GAL, GALR1 and NPY1R variants with opioid dependence

Aim: Heroin addiction is a chronic, relapsing disease that has genetic and environmental, including drug-induced, contributions. Stress influences the development of addictions. This study was conducted to determine if variants in stress-related genes are associated with opioid dependence (OD). Patients & methods: One hundred and twenty variants in 26 genes were analyzed in 597 Dutch subjects. Patients included 281 OD in methadone maintenance with or without heroin-assisted treatment and 316 controls. Results: Twelve SNPs in seven genes showed a nominally significant association with OD. Experiment-wise significant associations (p < 0.05) were found for three SNP pairs, through an interaction effect: NPY1R/GAL rs4691910/rs1893679, NPY1R/GAL rs4691910/rs3136541 and GALR1/GAL rs9807208/rs3136541. Conclusion: This study lends more evidence to previous reports of association of stress-related variants with heroin dependence.

A genome-wide case-only test for the detection of digenic inheritance in human exomes

Whole-exome sequencing (WES) has facilitated the discovery of genetic lesions underlying monogenic disorders. Incomplete penetrance and variable expressivity suggest a contribution of additional genetic lesions to clinical manifestations and outcome. Some monogenic disorders may therefore actually be digenic. However, only a few digenic disorders have been reported, all discovered by candidate gene approaches applied to at least one locus. We propose here a two-locus genome-wide test for detecting digenic inheritance in WES data. This approach uses the gene as the unit of analysis and tests all pairs of genes to detect pairwise gene × gene interactions underlying disease. It is a case-only method, which has several advantages over classic case-control tests, in particular by avoiding recruitment of controls. Our simulation studies based on real WES data identified two major sources of type I error inflation in this case-only test: linkage disequilibrium and population stratification. Both were corrected by specific procedures. Moreover, our case-only approach is more powerful than the corresponding case-control test for detecting digenic interactions in various population stratification scenarios. Finally, we confirmed the potential of our unbiased, genome-wide approach by successfully identifying a previously reported digenic lesion in patients with craniosynostosis. Our case-only test is a powerful and timely tool for detecting digenic inheritance in WES data from patients.

The missing heritability of familial colorectal cancer

Pinpointing heritability factors is fundamental for the prevention and early detection of cancer. Up to one-quarter of colorectal cancers (CRCs) occur in the context of familial aggregation of this disease, suggesting a strong genetic component. Currently, only less than half of the heritability of CRC can be attributed to hereditary syndromes or common risk loci. Part of the missing heritability of this disease may be explained by the inheritance of elusive high-risk variants, polygenic inheritance, somatic mosaicism, as well as shared environmental factors, among others. A great deal of the missing heritability in CRC is expected to be addressed in the coming years with the increased application of cutting-edge next-generation sequencing technologies, routine multigene panel testing and tumour-focussed germline predisposition screening approaches. On the other hand, it will be important to define the contribution of environmental factors to familial aggregation of CRC incidence. This review provides an overview of the known genetic causes of familial CRC and aims at providing clues that explain the missing heritability of this disease.