A resource to explore the discovery of rare diseases and their causative genes

Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases

The growth in breadth and depth of artificial intelligence (AI) applications has been fast, running hand in hand with the increasing amount of digital data available. Here, we comment on the application of AI in the field of drug development, with a strong focus on the specific achievements and challenges posed by rare diseases. Data paucity and high costs make drug development for rare diseases especially hard. AI can enable otherwise inaccessible approaches based on the large-scale integration of heterogeneous datasets and knowledge bases, guided by expert biological understanding. Obstacles still exist for the routine use of AI in the usually conservative pharmaceutical domain, which can easily become disillusioned. It is crucial to acknowledge that AI is a powerful, supportive tool that can assist but not replace human expertise in the various phases and aspects of drug discovery and development.

Heterozygous loss-of-function variants in DOCK4 cause neurodevelopmental delay and microcephaly

Neurons form the basic anatomical and functional structure of the nervous system, and defects in neuronal differentiation or formation of neurites are associated with various psychiatric and neurodevelopmental disorders. Dynamic changes in the cytoskeleton are essential for this process, which is, inter alia, controlled by the dedicator of cytokinesis 4 (DOCK4) through the activation of RAC1. Here, we clinically describe 7 individuals (6 males and one female) with variants in DOCK4 and overlapping phenotype of mild to severe global developmental delay. Additional symptoms include coordination or gait abnormalities, microcephaly, nonspecific brain malformations, hypotonia and seizures. Four individuals carry missense variants (three of them detected de novo) and three individuals carry null variants (two of them maternally inherited). Molecular modeling of the heterozygous missense variants suggests that the majority of them affect the globular structure of DOCK4. In vitro functional expression studies in transfected Neuro-2A cells showed that all missense variants impaired neurite outgrowth. Furthermore, Dock4 knockout Neuro-2A cells also exhibited defects in promoting neurite outgrowth. Our results, including clinical, molecular and functional data, suggest that loss-of-function variants in DOCK4 probable cause a variable spectrum of a novel neurodevelopmental disorder with microcephaly.

GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM

BACKGROUND

Thousands of genes have been associated with different Mendelian conditions. One of the valuable sources to track these gene-disease associations (GDAs) is the Online Mendelian Inheritance in Man (OMIM) database. However, most of the information in OMIM is textual, and heterogeneous (e.g. summarized by different experts), which complicates automated reading and understanding of the data. Here, we used Natural Language Processing (NLP) to make a tool (Gene-Phenotype Association Discovery (GPAD)) that could syntactically process OMIM text and extract the data of interest.

RESULTS

GPAD applies a series of language-based techniques to the text obtained from OMIM API to extract GDA discovery-related information. GPAD can inform when a particular gene was associated with a specific phenotype, as well as the type of validation-whether through model organisms or cohort-based patient-matching approaches-for such an association. GPAD extracted data was validated with published reports and was compared with large language model. Utilizing GPAD's extracted data, we analysed trends in GDA discoveries, noting a significant increase in their rate after the introduction of exome sequencing, rising from an average of about 150-250 discoveries each year. Contrary to hopes of resolving most GDAs for Mendelian disorders by now, our data indicate a substantial decline in discovery rates over the past five years (2017-2022). This decline appears to be linked to the increasing necessity for larger cohorts to substantiate GDAs. The rising use of zebrafish and Drosophila as model organisms in providing evidential support for GDAs is also observed.

CONCLUSIONS

GPAD's real-time analyzing capacity offers an up-to-date view of GDA discovery and could help in planning and managing the research strategies. In future, this solution can be extended or modified to capture other information in OMIM and scientific literature.

The Dangers of Acetaminophen for Neurodevelopment Outweigh Scant Evidence for Long-Term Benefits

Based on available data that include approximately 20 lines of evidence from studies in laboratory animal models, observations in humans, correlations in time, and pharmacological/toxicological considerations, it has been concluded without reasonable doubt and with no evidence to the contrary that exposure of susceptible babies and children to acetaminophen (paracetamol) induces many, if not most, cases of autism spectrum disorder (ASD). However, the relative number of cases of ASD that might be induced by acetaminophen has not yet been estimated. Here, we examine a variety of evidence, including the acetaminophen-induced reduction of social awareness in adults, the prevalence of ASD through time, and crude estimates of the relative number of ASD cases induced by acetaminophen during various periods of neurodevelopment. We conclude that the very early postpartum period poses the greatest risk for acetaminophen-induced ASD, and that nearly ubiquitous use of acetaminophen during early development could conceivably be responsible for the induction in the vast majority, perhaps 90% or more, of all cases of ASD. Despite over a decade of accumulating evidence that acetaminophen is harmful for neurodevelopment, numerous studies demonstrate that acetaminophen is frequently administered to children in excess of currently approved amounts and under conditions in which it provides no benefit. Further, studies have failed to demonstrate long-term benefits of acetaminophen for the pediatric population, leaving no valid rationale for continued use of the drug in that population given its risks to neurodevelopment.

Methylation analysis by targeted bisulfite sequencing in large for gestational age (LGA) newborns: the LARGAN cohort

BACKGROUND

In 1990, David Barker proposed that prenatal nutrition is directly linked to adult cardiovascular disease. Since then, the relationship between adult cardiovascular risk, metabolic syndrome and birth weight has been widely documented. Here, we used the TruSeq Methyl Capture EPIC platform to compare the methylation patterns in cord blood from large for gestational age (LGA) vs adequate for gestational age (AGA) newborns from the LARGAN cohort.

RESULTS

We found 1672 differentially methylated CpGs (DMCs) with a nominal p < 0.05 and 48 differentially methylated regions (DMRs) with a corrected p < 0.05 between the LGA and AGA groups. A systems biology approach identified several biological processes significantly enriched with genes in association with DMCs with FDR < 0.05, including regulation of transcription, regulation of epinephrine secretion, norepinephrine biosynthesis, receptor transactivation, forebrain regionalization and several terms related to kidney and cardiovascular development. Gene ontology analysis of the genes in association with the 48 DMRs identified several significantly enriched biological processes related to kidney development, including mesonephric duct development and nephron tubule development. Furthermore, our dataset identified several DNA methylation markers enriched in gene networks involved in biological pathways and rare diseases of the cardiovascular system, kidneys, and metabolism.

CONCLUSIONS

Our study identified several DMCs/DMRs in association with fetal overgrowth. The use of cord blood as a material for the identification of DNA methylation biomarkers gives us the possibility to perform follow-up studies on the same patients as they grow. These studies will not only help us understand how the methylome responds to continuum postnatal growth but also link early alterations of the DNA methylome with later clinical markers of growth and metabolic fitness.

Rare disease research resources at the Rat Genome Database

Rare diseases individually affect relatively few people, but as a group they impact considerable numbers of people. The Rat Genome Database (https://rgd.mcw.edu) is a knowledgebase that offers resources for rare disease research. This includes disease definitions, genes, quantitative trail loci (QTLs), genetic variants, annotations to published literature, links to external resources, and more. One important resource is identifying relevant cell lines and rat strains that serve as models for disease research. Diseases, genes, and strains have report pages with consolidated data, and links to analysis tools. Utilizing these globally accessible resources for rare disease research, potentiating discovery of mechanisms and new treatments, can point researchers toward solutions to alleviate the suffering of those afflicted with these diseases.

Activated PI3Kδ syndrome - reviewing challenges in diagnosis and treatment

Activated PI3Kδ syndrome (APDS) is a rare inborn error of immunity (IEI) characterized primarily by frequent infections, lymphoproliferation and autoimmunity. Since its initial description in 2013, APDS has become part of the growing group of nearly 500 IEIs affecting various components of the immune system. The two subtypes of APDS - APDS1 and APDS2 - are caused by variants in the PIK3CD and PIK3R1 genes, respectively. Due to the rarity of the disease and the heterogeneous clinical picture, many patients are not diagnosed until years after symptom onset. Another challenge is the large number of PIK3CD and PIK3R1 variants whose functional significance for developing APDS is inconclusive. Treatment of APDS has so far been mostly symptom-oriented with immunoglobulin replacement therapy, immunosuppressive therapies and antibiotic or antiviral prophylaxes. Additionally, allogeneic stem cell transplantation as well as new targeted therapies are options targeting the root cause that may improve patients' quality of life and life expectancy. However, the clinical course of the disease is difficult to predict which complicates the choice of appropriate therapies. This review article discusses diagnostic procedures and current and future treatment options, and highlights the difficulties that physicians, patients and their caretakers face in managing this complex disease. This article is based on cohort studies, the German and US guidelines on the management of primary immunodeficiencies as well as on published experience with diagnosis and compiled treatment experience for APDS.

Exploring the Potential Challenges for Developing Generic Orphan Drugs for Rare Diseases: A Survey of US and European Markets

OBJECTIVES

The US Food and Drug Administration in 1983 and the European Union's European Medicines Agency in 2000 implemented the orphan drug development program for rare diseases. The study aimed to find the potential challenges encountered by generic companies in developing generics for rare diseases.

METHODS

We performed a thematic analysis, which consists of qualitative and quantitative research. For data analysis of approved orphan drugs, we used statistical methods, and for the industrial case study, we selected 14 generic companies and conducted semistructured interviews related to 10 critical areas of drug development.

RESULTS

The orphan drug approvals were classified into 4 categories: the number of orphan approvals, pediatric claims, formulation, and therapeutic areas. We analyzed the approvals from 2001 to 2021; the Food and Drug Administration approved 815 drugs and European Medicines Agency approved 258 drugs. The pediatric orphan approvals were analyzed from 2010 to 2021; the average percentage of orphan drugs claim pediatric exclusivity during this period was found to be 31.8%. In formulation, we found the highest percentage of drugs belong to small molecules at 71%. In the therapeutic class, oncology drugs have a majority of approvals at 25%. The industrial case study responses revealed that the major challenge for drug development is the complexity of the disease at 21%, followed by the limited market at 17%.

CONCLUSIONS

There is a high need for generic orphan drugs in the developing countries. The generic companies can use the opportunities provided by health authorities for the benefit of both the company and the patient perspective.

Knowledge-based approaches to drug discovery for rare diseases

The conventional drug discovery pipeline has proven to be unsustainable for rare diseases. Herein, we discuss recent advances in biomedical knowledge mining applied to discovering therapeutics for rare diseases. We summarize current chemogenomics data of relevance to rare diseases and provide a perspective on the effectiveness of machine learning (ML) and biomedical knowledge graph mining in rare disease drug discovery. We illustrate the power of these methodologies using a chordoma case study. We expect that a broader application of knowledge graph mining and artificial intelligence (AI) approaches will expedite the discovery of viable drug candidates against both rare and common diseases.