Mendelian inheritance revisited: dominance and recessiveness in medical genetics

Clarifying Mendelian vs non-Mendelian inheritance

Gregor Mendel developed the principles of segregation and independent assortment in the mid-1800s based on his detailed analysis of several traits in pea plants. Those principles, now called Mendel's laws, in fact, explain the behavior of genes and alleles during meiosis and are now understood to underlie "Mendelian inheritance" of a wide range of traits and diseases across organisms. When asked to give examples of inheritance that do NOT follow Mendel's laws, in other words, examples of non-Mendelian inheritance, students sometimes list incomplete dominance, codominance, multiple alleles, sex-linked traits, and multigene traits and cite as their sources the Khan Academy, Wikipedia, and other online sites. Against this background, the goals of this Perspective are to (1) explain to students, healthcare workers, and other stakeholders why the examples above, in fact, display Mendelian inheritance, as they obey Mendel's laws of segregation and independent assortment, even though they do not produce classic Mendelian phenotypic ratios and (2) urge individuals with an intimate knowledge of genetic principles to monitor the accuracy of learning resources and work with us and those resources to correct information that is misleading.

Defective FGFR1 Signaling Disrupts Glucose Regulation: Evidence From Humans With FGFR1 Mutations

Context

Activation of fibroblast growth factor receptor 1 (FGFR1) signaling improves the metabolic health of animals and humans, while inactivation leads to diabetes in mice. Direct human genetic evidence for the role of FGFR1 signaling in human metabolic health has not been fully established.

Objective

We hypothesized that individuals with naturally occurring FGFR1 variants ("experiments of nature") will display glucose dysregulation.

Methods

Participants with rare FGFR1 variants and noncarrier controls. Using a recall-by-genotype approach, we examined the β-cell function and insulin sensitivity of 9 individuals with rare FGFR1 deleterious variants compared to 27 noncarrier controls, during a frequently sampled intravenous glucose tolerance test at the Reproductive Endocrine Unit and the Harvard Center for Reproductive Medicine, Massachusetts General Hospital. FGFR1-mutation carriers displayed higher β-cell function in the face of lower insulin sensitivity compared to controls.

Conclusion

These findings suggest that impaired FGFR1 signaling may contribute to an early insulin resistance phase of diabetes pathogenesis and support the candidacy of the FGFR1 signaling pathway as a therapeutic target for improving the human metabolic health.

Comparison of the ABC and ACMG systems for variant classification

The ABC and ACMG variant classification systems were compared by asking mainly European clinical laboratories to classify variants in 10 challenging cases using both systems, and to state if the variant in question would be reported as a relevant result or not as a measure of clinical utility. In contrast to the ABC system, the ACMG system was not made to guide variant reporting but to determine the likelihood of pathogenicity. Nevertheless, this comparison is justified since the ACMG class determines variant reporting in many laboratories. Forty-three laboratories participated in the survey. In seven cases, the classification system used did not influence the reporting likelihood when variants labeled as "maybe report" after ACMG-based classification were included. In three cases of population frequent but disease-associated variants, there was a difference in favor of reporting after ABC classification. A possible reason is that ABC step C (standard variant comments) allows a variant to be reported in one clinical setting but not another, e.g., based on Bayesian-based likelihood calculation of clinical relevance. Finally, the selection of ACMG criteria was compared between 36 laboratories. When excluding criteria used by less than four laboratories (<10%), the average concordance rate was 46%. Taken together, ABC-based classification is more clear-cut than ACMG-based classification since molecular and clinical information is handled separately, and variant reporting can be adapted to the clinical question and phenotype. Furthermore, variants do not get a clinically inappropriate label, like pathogenic when not pathogenic in a clinical context, or variant of unknown significance when the significance is known.

Altered chromatin topologies caused by balanced chromosomal translocation lead to central iris hypoplasia

Despite the advent of genomic sequencing, molecular diagnosis remains unsolved in approximately half of patients with Mendelian disorders, largely due to unclarified functions of noncoding regions and the difficulty in identifying complex structural variations. In this study, we map a unique form of central iris hypoplasia in a large family to 6q15-q23.3 and 18p11.31-q12.1 using a genome-wide linkage scan. Long-read sequencing reveals a balanced translocation t(6;18)(q22.31;p11.22) with intergenic breakpoints. By performing Hi-C on induced pluripotent stem cells from a patient, we identify two chromatin topologically associating domains spanning across the breakpoints. These alterations lead the ectopic chromatin interactions between APCDD1 on chromosome 18 and enhancers on chromosome 6, resulting in upregulation of APCDD1. Notably, APCDD1 is specifically localized in the iris of human eyes. Our findings demonstrate that noncoding structural variations can lead to Mendelian diseases by disrupting the 3D genome structure and resulting in altered gene expression.

Addressing diagnostic gaps and priorities of the global rare diseases community: Recommendations from the IRDiRC diagnostics scientific committee

The International Rare Diseases Research Consortium (IRDiRC) Diagnostic Scientific Committee (DSC) is charged with discussion and contribution to progress on diagnostic aspects of the IRDiRC core mission. Specifically, IRDiRC goals include timely diagnosis, use of globally coordinated diagnostic pipelines, and assessing the impact of rare diseases on affected individuals. As part of this mission, the DSC endeavored to create a list of research priorities to achieve these goals. We present a discussion of those priorities along with aspects of current, global rare disease needs and opportunities that support our prioritization. In support of this discussion, we also provide clinical vignettes illustrating real-world examples of diagnostic challenges.

Comparative analysis of in-silico tools in identifying pathogenic variants in dominant inherited retinal diseases

Inherited retinal diseases (IRDs) are a group of rare genetic eye conditions that cause blindness. Despite progress in identifying genes associated with IRDs, improvements are necessary for classifying rare autosomal dominant (AD) disorders. AD diseases are highly heterogenous, with causal variants being restricted to specific amino acid changes within certain protein domains, making AD conditions difficult to classify. Here, we aim to determine the top-performing in-silico tools for predicting the pathogenicity of AD IRD variants. We annotated variants from ClinVar and benchmarked 39 variant classifier tools on IRD genes, split by inheritance pattern. Using area-under-the-curve (AUC) analysis, we determined the top-performing tools and defined thresholds for variant pathogenicity. Top-performing tools were assessed using genome sequencing on a cohort of participants with IRDs of unknown etiology. MutScore achieved the highest accuracy within AD genes, yielding an AUC of 0.969. When filtering for AD gain-of-function and dominant negative variants, BayesDel had the highest accuracy with an AUC of 0.997. Five participants with variants in NR2E3, RHO, GUCA1A, and GUCY2D were confirmed to have dominantly inherited disease based on pedigree, phenotype, and segregation analysis. We identified two uncharacterized variants in GUCA1A (c.428T>A, p.Ile143Thr) and RHO (c.631C>G, p.His211Asp) in three participants. Our findings support using a multi-classifier approach comprised of new missense classifier tools to identify pathogenic variants in participants with AD IRDs. Our results provide a foundation for improved genetic diagnosis for people with IRDs.

De novo variants in SP9 cause a novel form of interneuronopathy characterized by intellectual disability, autism spectrum disorder, and epilepsy with variable expressivity

PURPOSE

Interneuronopathies are a group of neurodevelopmental disorders characterized by deficient migration and differentiation of gamma-aminobutyric acidergic interneurons resulting in a broad clinical spectrum, including autism spectrum disorders, early-onset epileptic encephalopathy, intellectual disability, and schizophrenic disorders. SP9 is a transcription factor belonging to the Krüppel-like factor and specificity protein family, the members of which harbor highly conserved DNA-binding domains. SP9 plays a central role in interneuron development and tangential migration, but it has not yet been implicated in a human neurodevelopmental disorder.

METHODS

Cases with SP9 variants were collected through international data-sharing networks. To address the specific impact of SP9 variants, in silico and in vitro assays were carried out.

RESULTS

De novo heterozygous variants in SP9 cause a novel form of interneuronopathy. SP9 missense variants affecting the glutamate 378 amino acid result in severe epileptic encephalopathy because of hypomorphic and neomorphic DNA-binding effects, whereas SP9 loss-of-function variants result in a milder phenotype with epilepsy, developmental delay, and autism spectrum disorder.

CONCLUSION

De novo heterozygous SP9 variants are responsible for a neurodevelopmental disease. Interestingly, variants located in conserved DNA-binding domains of KLF/SP family transcription factors may lead to neomorphic DNA-binding functions resulting in a combination of loss- and gain-of-function effects.

How do stochastic processes and genetic threshold effects explain incomplete penetrance and inform causal disease mechanisms?

Incomplete penetrance is the rule rather than the exception in Mendelian disease. In syndromic monogenic disorders, phenotypic variability can be viewed as the combination of incomplete penetrance for each of multiple independent clinical features. Within genetically identical individuals, such as isogenic model organisms, stochastic variation at molecular and cellular levels is the primary cause of incomplete penetrance according to a genetic threshold model. By defining specific probability distributions of causal biological readouts and genetic liability values, stochasticity and incomplete penetrance provide information about threshold values in biological systems. Ascertainment of threshold values has been achieved by simultaneous scoring of relatively simple phenotypes and quantitation of molecular readouts at the level of single cells. However, this is much more challenging for complex morphological phenotypes using experimental and reductionist approaches alone, where cause and effect are separated temporally and across multiple biological modes and scales. Here I consider how causal inference, which integrates observational data with high confidence causal models, might be used to quantify the relative contribution of different sources of stochastic variation to phenotypic diversity. Collectively, these approaches could inform disease mechanisms, improve predictions of clinical outcomes and prioritize gene therapy targets across modes and scales of gene function. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

BTB domain mutations perturbing KCTD15 oligomerisation cause a distinctive frontonasal dysplasia syndrome

INTRODUCTION

KCTD15 encodes an oligomeric BTB domain protein reported to inhibit neural crest formation through repression of Wnt/beta-catenin signalling, as well as transactivation by TFAP2. Heterozygous missense variants in the closely related paralogue KCTD1 cause scalp-ear-nipple syndrome.

METHODS

Exome sequencing was performed on a two-generation family affected by a distinctive phenotype comprising a lipomatous frontonasal malformation, anosmia, cutis aplasia of the scalp and/or sparse hair, and congenital heart disease. Identification of a de novo missense substitution within KCTD15 led to targeted sequencing of DNA from a similarly affected sporadic patient, revealing a different missense mutation. Structural and biophysical analyses were performed to assess the effects of both amino acid substitutions on the KCTD15 protein.

RESULTS

A heterozygous c.310G>C variant encoding p.(Asp104His) within the BTB domain of KCTD15 was identified in an affected father and daughter and segregated with the phenotype. In the sporadically affected patient, a de novo heterozygous c.263G>A variant encoding p.(Gly88Asp) was present in KCTD15. Both substitutions were found to perturb the pentameric assembly of the BTB domain. A crystal structure of the BTB domain variant p.(Gly88Asp) revealed a closed hexameric assembly, whereas biophysical analyses showed that the p.(Asp104His) substitution resulted in a monomeric BTB domain likely to be partially unfolded at physiological temperatures.

CONCLUSION

BTB domain substitutions in KCTD1 and KCTD15 cause clinically overlapping phenotypes involving craniofacial abnormalities and cutis aplasia. The structural analyses demonstrate that missense substitutions act through a dominant negative mechanism by disrupting the higher order structure of the KCTD15 protein complex.

Non-linear transcriptional responses to gradual modulation of transcription factor dosage

Genomic loci associated with common traits and diseases are typically non-coding and likely impact gene expression, sometimes coinciding with rare loss-of-function variants in the target gene. However, our understanding of how gradual changes in gene dosage affect molecular, cellular, and organismal traits is currently limited. To address this gap, we induced gradual changes in gene expression of four genes using CRISPR activation and inactivation. Downstream transcriptional consequences of dosage modulation of three master trans-regulators associated with blood cell traits (GFI1B, NFE2, and MYB) were examined using targeted single-cell multimodal sequencing. We showed that guide tiling around the TSS is the most effective way to modulate cis gene expression across a wide range of fold-changes, with further effects from chromatin accessibility and histone marks that differ between the inhibition and activation systems. Our single-cell data allowed us to precisely detect subtle to large gene expression changes in dozens of trans genes, revealing that many responses to dosage changes of these three TFs are non-linear, including non-monotonic behaviours, even when constraining the fold-changes of the master regulators to a copy number gain or loss. We found that the dosage properties are linked to gene constraint and that some of these non-linear responses are enriched for disease and GWAS genes. Overall, our study provides a straightforward and scalable method to precisely modulate gene expression and gain insights into its downstream consequences at high resolution.

Extended application of PGT-M strategies for small pathogenic CNVs

PURPOSE

The preimplantation genetic testing for aneuploidy (PGT-A) platform is not currently available for small copy-number variants (CNVs), especially those < 1 Mb. Through strategies used in PGT for monogenic disease (PGT-M), this study intended to perform PGT for families with small pathogenic CNVs.

METHODS

Couples who carried small pathogenic CNVs and underwent PGT at the Reproductive and Genetic Hospital of CITIC-Xiangya (Hunan, China) between November 2019 and April 2023 were included in this study. Haplotype analysis was performed through two platforms (targeted sequencing and whole-genome arrays) to identify the unaffected embryos, which were subjected to transplantation. Prenatal diagnosis using amniotic fluid was performed during 18-20 weeks of pregnancy.

RESULTS

PGT was successfully performed for 20 small CNVs (15 microdeletions and 5 microduplications) in 20 families. These CNVs distributed on chromosomes 1, 2, 6, 7, 13, 15, 16, and X with sizes ranging from 57 to 2120 kb. Three haplotyping-based PGT-M strategies were applied. A total of 89 embryos were identified in 25 PGT cycles for the 20 families. The diagnostic yield was 98.9% (88/89). Nineteen transfers were performed for 17 women, resulting in a 78.9% (15/19) clinical pregnancy rate after each transplantation. Of the nine women who had healthy babies, eight accepted prenatal diagnosis and the results showed no related pathogenic CNVs.

CONCLUSION

Our results show that the extended haplotyping-based PGT-M strategy application for small pathogenic CNVs compensated for the insufficient resolution of PGT-A. These three PGT-M strategies could be applied to couples with small pathogenic CNVs.

The genetic and molecular basis of haploinsufficiency in flowering plants

In diploid organisms, haploinsufficiency can be defined as the requirement for more than one fully functional copy of a gene. In contrast to most genes, whose loss-of-function alleles are recessive, loss-of-function alleles of haploinsufficient genes are dominant. However, forward and reverse genetic screens are biased toward obtaining recessive, loss-of-function mutations, and therefore, dominant mutations of all types are underrepresented in mutant collections. Despite this underrepresentation, haploinsufficient loci have intriguing implications for studies of genome evolution, gene dosage, stability of protein complexes, genetic redundancy, and gene expression. Here we review examples of haploinsufficiency in flowering plants and describe the underlying molecular mechanisms and evolutionary forces driving haploinsufficiency. Finally, we discuss the masking of haploinsufficiency by genetic redundancy, a widespread phenomenon among angiosperms.

Statistical Dissection of the Genetic Determinants of Phenotypic Heterogeneity in Genes with Multiple Associated Rare Diseases

Phenotypicheterogeneity is a phenomenon in which distinct phenotypes can develop in individuals bearing pathogenic variants in the same gene. Genetic factors, gene interactions, and environmental factors are usually considered the key mechanisms of this phenomenon. Phenotypic heterogeneity may impact the prognosis of the disease severity and symptoms. In our work, we used publicly available data on the association between genetic variants and Mendelian disease to investigate the genetic factors (such as the intragenic localization and type of a variant) driving the heterogeneity of gene-disease relationships. First, we showed that genes linked to multiple rare diseases (GMDs) are more constrained and tend to encode more transcripts with high levels of expression across tissues. Next, we assessed the role of variant localization and variant types in specifying the exact phenotype for GMD variants. We discovered that none of these factors is sufficient to explain the phenomenon of such heterogeneous gene-disease relationships. In total, we identified only 38 genes with a weak trend towards significant differences in variant localization and 30 genes with nominal significant differences in variant type for the two associated disorders. Remarkably, four of these genes showed significant differences in both tests. At the same time, our analysis suggests that variant localization and type are more important for genes linked to autosomal dominant disease. Taken together, our results emphasize the gene-level factors dissecting distinct Mendelian diseases linked to one common gene based on open-access genetic data and highlight the importance of exploring other factors that contributed to phenotypic heterogeneity.

Exploring the complex spectrum of dominance and recessiveness in genetic cardiomyopathies

Discrete categorization of Mendelian disease genes into dominant and recessive models often oversimplifies their underlying genetic architecture. Cardiomyopathies (CMs) are genetic diseases with complex etiologies for which an increasing number of recessive associations have recently been proposed. Here, we comprehensively analyze all published evidence pertaining to biallelic variation associated with CM phenotypes to identify high-confidence recessive genes and explore the spectrum of monoallelic and biallelic variant effects in established recessive and dominant disease genes. We classify 18 genes with robust recessive association with CMs, largely characterized by dilated phenotypes, early disease onset and severe outcomes. Several of these genes have monoallelic association with disease outcomes and cardiac traits in the UK Biobank, including LMOD2 and ALPK3 with dilated and hypertrophic CM, respectively. Our data provide insights into the complex spectrum of dominance and recessiveness in genetic heart disease and demonstrate how such approaches enable the discovery of unexplored genetic associations.

Nature and nurture: understanding phenotypic variation in inborn errors of immunity

The overall disease burden of pediatric infection is high, with widely varying clinical outcomes including death. Among the most vulnerable children, those with inborn errors of immunity, reduced penetrance and variable expressivity are common but poorly understood. There are several genetic mechanisms that influence phenotypic variation in inborn errors of immunity, as well as a body of knowledge on environmental influences and specific pathogen triggers. Critically, recent advances are illuminating novel nuances for fundamental concepts on disease penetrance, as well as raising new areas of inquiry. The last few decades have seen the identification of almost 500 causes of inborn errors of immunity, as well as major advancements in our ability to characterize somatic events, the microbiome, and genotypes across large populations. The progress has not been linear, and yet, these developments have accumulated into an enhanced ability to diagnose and treat inborn errors of immunity, in some cases with precision therapy. Nonetheless, many questions remain regarding the genetic and environmental contributions to phenotypic variation both within and among families. The purpose of this review is to provide an updated summary of key concepts in genetic and environmental contributions to phenotypic variation within inborn errors of immunity, conceptualized as including dynamic, reciprocal interplay among factors unfolding across the key dimension of time. The associated findings, potential gaps, and implications for research are discussed in turn for each major influencing factor. The substantial challenge ahead will be to organize and integrate information in such a way that accommodates the heterogeneity within inborn errors of immunity to arrive at a more comprehensive and accurate understanding of how the immune system operates in health and disease. And, crucially, to translate this understanding into improved patient care for the millions at risk for serious infection and other immune-related morbidity.

An RNA-informed dosage sensitivity map reflects the intrinsic functional nature of genes

Understanding dosage sensitivity or why Mendelian diseases have dominant vs. recessive modes of inheritance is crucial for uncovering the etiology of human disease. Previous knowledge of dosage sensitivity is mainly based on observations of rare loss-of-function mutations or copy number changes, which are underpowered due to ultra rareness of such variants. Thus, the functional underpinnings of dosage constraint remain elusive. In this study, we aim to systematically quantify dosage perturbations from cis-regulatory variants in the general population to yield a tissue-specific dosage constraint map of genes and further explore their underlying functional logic. We reveal an inherent divergence of dosage constraints in genes by functional categories with signaling genes (transcription factors, protein kinases, ion channels, and cellular machinery) being dosage sensitive, while effector genes (transporters, metabolic enzymes, cytokines, and receptors) are generally dosage resilient. Instead of being a metric of functional dispensability, we show that dosage constraint reflects underlying homeostatic constraints arising from negative feedback. Finally, we employ machine learning to integrate DNA and RNA metrics to generate a comprehensive, tissue-specific map of dosage sensitivity (MoDs) for autosomal genes.

Genetic diversity and population structure of Polygonatum cyrtonema Hua in China using SSR markers

Polygonatum cyrtonema Hua is a perennial herbaceous plant of the Polygonatum genus, belonging to the Liliaceae family, with significant medicinal and nutritional value. In China, this species is a traditional medicinal and edible herb with a long history of application and is widely appreciated by the people. However, as the demand for medicinal herbs continues to grow, excessive harvesting has led to the depletion of wild resources and the risk of genetic erosion. In addition, the chaotic cultivation of varieties and the lack of high quality germplasm resources have led to inconsistent quality of medical materials. Therefore, it is urgent to conduct genetic diversity evaluation of this species and establish a sound conservation plan. This study assessed the genetic diversity and population structure of 96 samples collected from seven regions in China using the simple sequence repeat (SSR) molecular marker technology. In this study, a total of 60 alleles (Na) were detected across the 10 polymorphic SSR markers used, with an average of 6.0 alleles generated per locus. The values of polymorphic information content (PIC) values ranged from 0.3396 to 0.8794, with an average value of 0.6430. The average value of the effective number of alleles (Ne) was 2.761, and the average value of the Shannon's information index (I) was 1.196. The population structure analysis indicates that the Polygonatum cyrtonema Hua germplasm can be classified into three subpopulations (JZ, QY, JD) at the molecular level, which corresponds to the previous subgroups identified based on individual plant phenotypic traits. Analysis of Molecular Variance (AMOVA) showed that 74% of the genetic variation was between individuals within populations in different regions. The phylogenetic analysis of the 96 germplasm samples divided them into three main populations. The QY and JD subpopulations are largely clustered together, which could be attributed to their mountainous distribution and the local climate environment. The genetic differentiation coefficient (Fst) value was low at 0.065, indicating relatively low population differentiation. The ratio of the genetic differentiation coefficient (Fst) between the JZ population and the other two populations (QY and JD) is much higher than the ratio between the QY and JD populations. Based on the clustering results and the ratio of the genetic differentiation coefficient (Fst), it can be inferred that the genetic relationship between the QY and JD subpopulations is closer, with a certain degree of genetic differentiation from the JZ subpopulation. This study supports the conservation of germplasm resources of Polygonatum cyrtonema Hua in China and provides new parental material for germplasm genetic improvement and breeding programs.

At-Risk Genomic Findings for Pediatric-Onset Disorders From Genome Sequencing vs Medically Actionable Gene Panel in Proactive Screening of Newborns and Children

Importance

Although the clinical utility of genome sequencing for critically ill children is well recognized, its utility for proactive pediatric screening is not well explored.

Objective

To evaluate molecular findings from screening ostensibly healthy children with genome sequencing compared with a gene panel for medically actionable pediatric conditions.

Design, Setting, and Participants

This case series study was conducted among consecutive, apparently healthy children undergoing proactive genetic screening for pediatric disorders by genome sequencing (n = 562) or an exome-based panel of 268 genes (n = 606) from March 1, 2018, through July 31, 2022.

Exposures

Genetic screening for pediatric-onset disorders using genome sequencing or an exome-based panel of 268 genes.

Main Outcomes and Measures

Molecular findings indicative of genetic disease risk.

Results

Of 562 apparently healthy children (286 girls [50.9%]; median age, 29 days [IQR, 9-117 days]) undergoing screening by genome sequencing, 46 (8.2%; 95% CI, 5.9%-10.5%) were found to be at risk for pediatric-onset disease, including 22 children (3.9%) at risk for high-penetrance disorders. Sequence analysis uncovered molecular diagnoses among 32 individuals (5.7%), while copy number variant analysis uncovered molecular diagnoses among 14 individuals (2.5%), including 4 individuals (0.7%) with chromosome scale abnormalities. Overall, there were 47 molecular diagnoses, with 1 individual receiving 2 diagnoses; of the 47 potential diagnoses, 22 (46.8%) were associated with high-penetrance conditions. Pathogenic variants in medically actionable pediatric genes were found in 6 individuals (1.1%), constituting 12.8% (6 of 47) of all diagnoses. At least 1 pharmacogenomic variant was reported for 89.0% (500 of 562) of the cohort. In contrast, of 606 children (293 girls [48.3%]; median age, 26 days [IQR, 10-67 days]) undergoing gene panel screening, only 13 (2.1%; 95% CI, 1.0%-3.3%) resulted in potential childhood-onset diagnoses, a significantly lower rate than those screened by genome sequencing (P < .001).

Conclusions and Relevance

In this case series study, genome sequencing as a proactive screening approach for children, due to its unrestrictive gene content and technical advantages in comparison with an exome-based gene panel for medically actionable childhood conditions, uncovered a wide range of heterogeneous high-penetrance pediatric conditions that could guide early interventions and medical management.