Deep learning modeling of rare noncoding genetic variants in human motor neurons defines CCDC146 as a therapeutic target for ALS.

Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease caused by the selective and progressive death of motor neurons (MNs). Understanding the genetic and molecular factors influencing ALS survival is crucial for disease management and therapeutics. In this study, we introduce a deep learning-powered genetic analysis framework to link rare noncoding genetic variants to ALS survival. Using data from human induced pluripotent stem cell (iPSC)-derived MNs, this method prioritizes functional noncoding variants using deep learning, links cis-regulatory elements (CREs) to target genes using epigenomics data, and integrates these data through gene-level burden tests to identify survival-modifying variants, CREs, and genes. We apply this approach to analyze 6,715 ALS genomes, and pinpoint four novel rare noncoding variants associated with survival, including chr7:76,009,472:C>T linked to CCDC146. CRISPR-Cas9 editing of this variant increases CCDC146 expression in iPSC-derived MNs and exacerbates ALS-specific phenotypes, including TDP-43 mislocalization. Suppressing CCDC146 with an antisense oligonucleotide (ASO), showing no toxicity, completely rescues ALS-associated survival defects in neurons derived from sporadic ALS patients and from carriers of the ALS-associated G4C2-repeat expansion within C9ORF72. ASO targeting of CCDC146 may be a broadly effective therapeutic approach for ALS. Our framework provides a generic and powerful approach for studying noncoding genetics of complex human diseases.

Recently Evolved Enhancers Emerge with High Interindividual Variability and Less Frequently Associate with Disease.

Mutations in non-coding regulatory DNA such as enhancers underlie a wide variety of diseases including developmental disorders and cancer. As enhancers rapidly evolve, understanding their function and configuration in non-human disease models can have important clinical applications. Here, we analyze enhancer configurations in tissues isolated from the common marmoset, a widely used primate model for human disease. Integrating these data with human and mouse data, we find that enhancers containing trait-associated variants are preferentially conserved. In contrast, most human-specific enhancers are highly variable between individuals, with a subset failing to contact promoters. These are located further away from genes and more often reside in inactive B-compartments. Our data show that enhancers typically emerge as instable elements with minimal biological impact prior to their integration in a transcriptional program. Furthermore, our data provide insight into which trait variations in enhancers can be faithfully modeled using the common marmoset.

Hominin-specific regulatory elements selectively emerged in oligodendrocytes and are disrupted in autism patients.

Speciation is associated with substantial rewiring of the regulatory circuitry underlying the expression of genes. Determining which changes are relevant and underlie the emergence of the human brain or its unique susceptibility to neural disease has been challenging. Here we annotate changes to gene regulatory elements (GREs) at cell type resolution in the brains of multiple primate species spanning most of primate evolution. We identify a unique set of regulatory elements that emerged in hominins prior to the separation of humans and chimpanzees. We demonstrate that these hominin gains perferentially affect oligodendrocyte function postnatally and are preferentially affected in the brains of autism patients. This preference is also observed for human-specific GREs suggesting this system is under continued selective pressure. Our data provide a roadmap of regulatory rewiring across primate evolution providing insight into the genomic changes that underlie the emergence of the brain and its susceptibility to neural disease.