Identification of novel candidate risk genes for myelomeningocele within the glucose homeostasis/oxidative stress and folate/one-carbon metabolism networks

ARMC5 controls the degradation of most Pol II subunits, and ARMC5 mutation increases neural tube defect risks in mice and humans

BACKGROUND

Neural tube defects (NTDs) are caused by genetic and environmental factors. ARMC5 is part of a novel ubiquitin ligase specific for POLR2A, the largest subunit of RNA polymerase II (Pol II).

RESULTS

We find that ARMC5 knockout mice have increased incidence of NTDs, such as spina bifida and exencephaly. Surprisingly, the absence of ARMC5 causes the accumulation of not only POLR2A but also most of the other 11 Pol II subunits, indicating that the degradation of the whole Pol II complex is compromised. The enlarged Pol II pool does not lead to generalized Pol II stalling or a generalized decrease in mRNA transcription. In neural progenitor cells, ARMC5 knockout only dysregulates 106 genes, some of which are known to be involved in neural tube development. FOLH1, critical in folate uptake and hence neural tube development, is downregulated in the knockout intestine. We also identify nine deleterious mutations in the ARMC5 gene in 511 patients with myelomeningocele, a severe form of spina bifida. These mutations impair the interaction between ARMC5 and Pol II and reduce Pol II ubiquitination.

CONCLUSIONS

Mutations in ARMC5 increase the risk of NTDs in mice and humans. ARMC5 is part of an E3 controlling the degradation of all 12 subunits of Pol II under physiological conditions. The Pol II pool size might have effects on NTD pathogenesis, and some of the effects might be via the downregulation of FOLH1. Additional mechanistic work is needed to establish the causal effect of the findings on NTD pathogenesis.

Unraveling the complex genetics of neural tube defects: From biological models to human genomics and back

Neural tube defects (NTDs) are a classic example of preventable birth defects for which there is a proven-effective intervention, folic acid (FA); however, further methods of prevention remain unrealized. In the decades following implementation of FA nutritional fortification programs throughout at least 87 nations, it has become apparent that not all NTDs can be prevented by FA. In the United States, FA fortification only reduced NTD rates by 28-35% (Williams et al., 2015). As such, it is imperative that further work is performed to understand the risk factors associated with NTDs and their underlying mechanisms so that alternative prevention strategies can be developed. However, this is complicated by the sheer number of genes associated with neural tube development, the heterogeneity of observable phenotypes in human cases, the rareness of the disease, and the myriad of environmental factors associated with NTD risk. Given the complex genetic architecture underlying NTD pathology and the way in which that architecture interacts dynamically with environmental factors, further prevention initiatives will undoubtedly require precision medicine strategies that utilize the power of human genomics and modern tools for assessing genetic risk factors. Herein, we review recent advances in genomic strategies for discovering genetic variants associated with these defects, and new ways in which biological models, such as mice and cell culture-derived organoids, are leveraged to assess mechanistic functionality, the way these variants interact with other genetic or environmental factors, and their ultimate contribution to human NTD risk.

Human myelomeningocele risk and ultra-rare deleterious variants in genes associated with cilium, WNT-signaling, ECM, cytoskeleton and cell migration

Myelomeningocele (MMC) affects one in 1000 newborns annually worldwide and each surviving child faces tremendous lifetime medical and caregiving burdens. Both genetic and environmental factors contribute to disease risk but the mechanism is unclear. This study examined 506 MMC subjects for ultra-rare deleterious variants (URDVs, absent in gnomAD v2.1.1 controls that have Combined Annotation Dependent Depletion score ≥ 20) in candidate genes either known to cause abnormal neural tube closure in animals or previously associated with human MMC in the current study cohort. Approximately 70% of the study subjects carried one to nine URDVs among 302 candidate genes. Half of the study subjects carried heterozygous URDVs in multiple genes involved in the structure and/or function of cilium, cytoskeleton, extracellular matrix, WNT signaling, and/or cell migration. Another 20% of the study subjects carried heterozygous URDVs in candidate genes associated with gene transcription regulation, folate metabolism, or glucose metabolism. Presence of URDVs in the candidate genes involving these biological function groups may elevate the risk of developing myelomeningocele in the study cohort.

Multifactorial Rare Diseases: Can Uncertainty Analysis Bring Added Value to the Search for Risk Factors and Etiopathogenesis?

Uncertainty analysis is the process of identifying limitations in knowledge and evaluating their implications for scientific conclusions. Uncertainty analysis is a stable component of risk assessment and is increasingly used in decision making on complex health issues. Uncertainties should be identified in a structured way and prioritized according to their likely impact on the outcome of scientific conclusions. Uncertainty is inherent to the rare diseases (RD) area, where research and healthcare have to cope with knowledge gaps due to the rarity of the conditions; yet a systematic approach toward uncertainties is not usually undertaken. The uncertainty issue is particularly relevant to multifactorial RD, whose etiopathogenesis involves environmental factors and genetic predisposition. Three case studies are presented: the newly recognized acute multisystem inflammatory syndrome in children and adolescents associated with SARS-CoV-2 infection; the assessment of risk factors for neural tube defects; and the genotype-phenotype correlation in familial Mediterranean fever. Each case study proposes the initial identification of the main epistemic and sampling uncertainties and their impacts. Uncertainty analysis in RD may present aspects similar to those encountered when conducting risk assessment in data-poor scenarios; therefore, approaches such as expert knowledge elicitation may be considered. The RD community has a main strength in managing uncertainty, as it proactively develops stakeholder involvement, data sharing and open science. The open science approaches can be profitably integrated by structured uncertainty analysis, especially when dealing with multifactorial RD involving environmental and genetic risk factors.