A novel ISLR2-linked autosomal recessive syndrome of congenital hydrocephalus, arthrogryposis and abdominal distension

Arab founder variants: Contributions to clinical genomics and precision medicine

BACKGROUND

Founder variants are ancestral variants shared by individuals who are not closely related. The large effect size of some of these variants in the context of Mendelian disorders offers numerous precision medicine opportunities.

METHODS

Using one of the largest datasets on Mendelian disorders in the Middle East, we identified 2,908 medically relevant founder variants derived from 18,360 exomes and genomes and investigated their contribution to the clinical annotation of the human genome.

FINDINGS

Strikingly, ∼34% of Arab founder variants are absent in gnomAD. We found a strong contribution of Arab founder variants to the identification of novel gene-disease links (n = 224) and the support/dispute (n = 81 support, n = 101 dispute) of previously reported candidate gene-disease links. The powerful segregation evidence generated by Arab founder variants allowed many ClinVar and Human Gene Mutation Database variants to be reclassified. Overall, 39.5% of diagnostic reports from our clinical lab are based on founder variants, and 19.41% of tested individuals carry at least one pathogenic founder variant. The presumptive loss-of-function mechanism that typically underlies autosomal recessive diseases means that Arab founder variants also offer unique opportunities in "druggable genome" research. Arab founder variants were also informative of migration patterns in the Middle East consistent with documented historical accounts.

CONCLUSIONS

We highlight the contribution of founder variants from an under-represented population group to precision medicine and inform future prevention programs. Our study also sheds light on the added value of these variants in supplementing other lines of research in tracing population history.

FUNDING

There is no funding for this work.

Prenatal diagnosis of a 15q24.1 microdeletion in a fetus with cerebral and urogenital abnormalities

15q24.1 microdeletion syndrome is a recently described condition often resulting from non-allelic homologous recombination (NAHR). Typical clinical features include pre and post-natal growth retardation, facial dysmorphism, developmental delay and intellectual disability. Nonspecific urogenital, skeletal, and digit abnormalities may be present, although other congenital malformations are less frequent. Consequently, only one case was reported prenatally, complicating the genotype-phenotype correlation and the genetic counseling. We identified prenatally a second case, presenting with cerebral abnormalities including hydrocephaly, macrocephaly, cerebellum hypoplasia, vermis hypoplasia, rhombencephalosynapsis, right kidney agenesis with left kidney duplication and micropenis. Genome-wide aCGH assay allowed a diagnosis at 26 weeks of amenorrhea revealing a 1.6 Mb interstitial deletion on the long arm of chromosome 15 at 15q24.1-q24.2 (arr[GRCh37] 15q24.1q24.2(74,399,112_76,019,966)x1). A deep review of the literature was undertaken to further delineate the prenatal clinical features and the candidate genes involved in the phenotype. Cerebral malformations are typically nonspecific, but microcephaly appears to be the most frequent in postnatal cases. Our case is the first reported with a frank cerebellar involvement.

Predicting Outcomes of Preterm Neonates Post Intraventricular Hemorrhage

Intraventricular hemorrhage (IVH) in preterm neonates presents a high risk for developing posthemorrhagic ventricular dilatation (PHVD), a severe complication that can impact survival and long-term outcomes. Early detection of PHVD before clinical onset is crucial for optimizing therapeutic interventions and providing accurate parental counseling. This study explores the potential of explainable machine learning models based on targeted liquid biopsy proteomics data to predict outcomes in preterm neonates with IVH. In recent years, research has focused on leveraging advanced proteomic technologies and machine learning to improve prediction of neonatal complications, particularly in relation to neurological outcomes. Machine learning (ML) approaches, combined with proteomics, offer a powerful tool to identify biomarkers and predict patient-specific risks. However, challenges remain in integrating large-scale, multiomic datasets and translating these findings into actionable clinical tools. Identifying reliable, disease-specific biomarkers and developing explainable ML models that clinicians can trust and understand are key barriers to widespread clinical adoption. In this prospective longitudinal cohort study, we analyzed 1109 liquid biopsy samples from 99 preterm neonates with IVH, collected at up to six timepoints over 13 years. Various explainable ML techniques-including statistical, regularization, deep learning, decision trees, and Bayesian methods-were employed to predict PHVD development and survival and to discover disease-specific protein biomarkers. Targeted proteomic analyses were conducted using serum and urine samples through a proximity extension assay capable of detecting low-concentration proteins in complex biofluids. The study identified 41 significant independent protein markers in the 1600 calculated ML models that surpassed our rigorous threshold (AUC-ROC of ≥0.7, sensitivity ≥ 0.6, and selectivity ≥ 0.6), alongside gestational age at birth, as predictive of PHVD development and survival. Both known biomarkers, such as neurofilament light chain (NEFL), and novel biomarkers were revealed. These findings underscore the potential of targeted proteomics combined with ML to enhance clinical decision-making and parental counseling, though further validation is required before clinical implementation.

Antenatal steroids elicited neurodegenerative-associated transcriptional changes in the hippocampus of preterm fetal sheep independent of lung maturation

BACKGROUND

Antenatal steroid therapy for fetal lung maturation is routinely administered to women at risk of preterm delivery. There is strong evidence to demonstrate benefit from antenatal steroids in terms of survival and respiratory disease, notably in infants delivered at or below 32 weeks' gestation. However, dosing remains unoptimized and lung benefits are highly variable. Current treatment regimens generate high-concentration, pulsatile fetal steroid exposures now associated with increased risk of childhood neurodevelopmental diseases. We hypothesized that damage-associated changes in the fetal hippocampal transcriptome would be independent of preterm lung function.

METHODS

Date-mated ewes carrying a single fetus at 122 ± 2dGA (term = 150dGA) were randomized into 4 groups: (i) Saline Control Group, 4×2ml maternal saline intramuscular(IM) injections at 12hr intervals (n = 11); or (ii) Dex High Group, 2×12mg maternal IM dexamethasone phosphate injections at 12hr intervals followed by 2×2ml IM saline injections at 12hr intervals (n = 12; representing a clinical regimen used in Singapore); or (iii) Dex Low Group, 4×1.5mg maternal IM dexamethasone phosphate injections 12hr intervals (n = 12); or (iv) Beta-Acetate Group, 1×0.125mg/kg maternal IM betamethasone acetate injection followed by 3×2ml IM sterile normal saline injections 12hr intervals (n = 8). Lambs were surgically delivered 48hr after first maternal injection at 122-125dGA, ventilated for 30min to establish lung function, and euthanised for necropsy and tissue collection.

RESULTS

Preterm lambs from the Dex Low and Beta-Acetate Groups had statistically and biologically significant lung function improvements (measured by gas exchange, lung compliance). Compared to the Saline Control Group, hippocampal transcriptomic data identified 879 differentially significant expressed genes (at least 1.5-fold change and FDR < 5%) in the steroid-treated groups. Pulsatile dexamethasone-only exposed groups (Dex High and Dex Low) had three common positively enriched differentially expressed pathways related in part to neurodegeneration ("Prion Disease", "Alzheimer's Disease", "Arachidonic Acid metabolism"). Adverse changes were independent of respiratory function during ventilation.

CONCLUSIONS

Our data suggests that exposure to antenatal steroid therapy is an independent cause of damage- associated transcriptomic changes in the brain of preterm, fetal sheep. These data highlight an urgent need for careful reconsideration and balancing of how antenatal steroids are used, both for patient selection and dosing regimens.

Molecular signatures of normal pressure hydrocephalus: a large-scale proteomic analysis of cerebrospinal fluid

Given the persistent challenge of differentiating idiopathic Normal Pressure Hydrocephalus (iNPH) from similar clinical entities, we conducted an in-depth proteomic study of cerebrospinal fluid (CSF) in 28 shunt-responsive iNPH patients, 38 Mild Cognitive Impairment (MCI) due to Alzheimer's disease, and 49 healthy controls. Utilizing the Olink Explore 3072 panel, we identified distinct proteomic profiles in iNPH that highlight significant downregulation of synaptic markers and cell-cell adhesion proteins. Alongside vimentin and inflammatory markers upregulation, these results suggest ependymal layer and transependymal flow dysfunction. Moreover, downregulation of multiple proteins associated with congenital hydrocephalus (e.g., L1CAM, PCDH9, ISLR2, ADAMTSL2, and B4GAT1) points to a possible shared molecular foundation between congenital hydrocephalus and iNPH. Through orthogonal partial least squares discriminant analysis (OPLS-DA), a panel comprising 13 proteins has been identified as potential diagnostic biomarkers of iNPH, pending external validation. These findings offer novel insights into the pathophysiology of iNPH, with implications for improved diagnosis.

Molecular Signatures of Normal Pressure Hydrocephalus: A Largescale Proteomic Analysis of Cerebrospinal Fluid

Given the persistent challenge of differentiating idiopathic Normal Pressure Hydrocephalus (iNPH) from similar clinical entities, we conducted an in-depth proteomic study of cerebrospinal fluid (CSF) in 28 shunt-responsive iNPH patients, 38 Mild Cognitive Impairment (MCI) due to Alzheimer's disease, and 49 healthy controls. Utilizing the Olink Explore 3072 panel, we identified distinct proteomic profiles in iNPH that highlight significant downregulation of synaptic markers and cell-cell adhesion proteins. Alongside vimentin and inflammatory markers upregulation, these results suggest ependymal layer and transependymal flow dysfunction. Moreover, downregulation of multiple proteins associated with congenital hydrocephalus (e.g., L1CAM, PCDH9, ISLR2, ADAMTSL2, and B4GAT1) points to a possible shared molecular foundation between congenital hydrocephalus and iNPH. Through orthogonal partial least squares discriminant analysis (OPLS-DA), a panel comprising 13 proteins has been identified as potential diagnostic biomarkers of iNPH, pending external validation. These findings offer novel insights into the pathophysiology of iNPH, with implications for improved diagnosis.

The genetic basis of hydrocephalus: genes, pathways, mechanisms, and global impact

Hydrocephalus (HC) is a heterogenous disease characterized by alterations in cerebrospinal fluid (CSF) dynamics that may cause increased intracranial pressure. HC is a component of a wide array of genetic syndromes as well as a secondary consequence of brain injury (intraventricular hemorrhage (IVH), infection, etc.) that can present across the age spectrum, highlighting the phenotypic heterogeneity of the disease. Surgical treatments include ventricular shunting and endoscopic third ventriculostomy with or without choroid plexus cauterization, both of which are prone to failure, and no effective pharmacologic treatments for HC have been developed. Thus, there is an urgent need to understand the genetic architecture and molecular pathogenesis of HC. Without this knowledge, the development of preventive, diagnostic, and therapeutic measures is impeded. However, the genetics of HC is extraordinarily complex, based on studies of varying size, scope, and rigor. This review serves to provide a comprehensive overview of genes, pathways, mechanisms, and global impact of genetics contributing to all etiologies of HC in humans.

KIF26A is mutated in the syndrome of congenital hydrocephalus with megacolon

Human disorders of the enteric nervous system (ENS), e.g., Hirschsprung's disease, are rarely associated with major central nervous system involvement. We describe two families each segregating a different homozygous truncating variant in KIF26A with a unique constellation of severe megacolon that resembles Hirschsprung's disease but lacks aganglionosis as well as brain malformations that range from severe to mild. The intestinal phenotype bears a striking resemblance to that observed in Kif26a^-/- mice where KIF26A deficiency was found to cause abnormal GDNF-Ret signaling resulting in failure to establish normal neuronal networks despite myenteric neuronal hyperplasia. Very recently, a range of brain developmental phenotypes were described in patients and mice with KIF26A deficiency and were found to result from abnormal radial migration and increased apoptosis. Our report, therefore, reveals a recognizable autosomal-recessive human KIF26A deficiency phenotype characterized by severe ENS dysfunction and a range of brain malformations.

Genes causing congenital hydrocephalus: Their chromosomal characteristics of telomere proximity and DNA compositions

Congenital hydrocephalus (CH) is caused by genetic mutations, but whether factors impacting human genetic mutations are disease-specific remains elusive. Given two factors associated with high mutation rates, we reviewed how many disease-susceptible genes match with (i) proximity to telomeres or (ii) high adenine and thymine (A + T) content in human CH as compared to other disorders of the central nervous system (CNS). We extracted genomic information using a genome data viewer. Importantly, 98 of 108 genes causing CH satisfied (i) or (ii), resulting in >90% matching rate. However, such a high accordance no longer sustained as we checked two factors in Alzheimer's disease (AD) and/or familial Parkinson's disease (fPD), resulting in 84% and 59% matching, respectively. A disease-specific matching of telomere proximity or high A + T content predicts causative genes of CH much better than neurodegenerative diseases and other CNS conditions, likely due to sufficient number of known causative genes (n = 108) and precise determination and classification of the genotype and phenotype. Our analysis suggests a need for identifying genetic basis of both factors before human clinical studies, to prioritize putative genes found in preclinical models into the likely (meeting at least one) and more likely candidate (meeting both), which predisposes human genes to mutations.