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1.
Hum Mol Genet ; 31(11): 1733-1746, 2022 06 04.
Artículo en Inglés | MEDLINE | ID: mdl-34888668

RESUMEN

A highly evolutionarily conserved myeloid ecotropic viral integration site 1 (MEIS1) intronic region is strongly associated with restless legs syndrome (RLS) and insomnia. To understand its regulatory function, we dissected the region by analyzing chromatin accessibility, enhancer-promoter contacts, DNA methylation and expression quantitative trait locus (eQTLs) in different human neural cell types and tissues. We observed specific activity with respect to cell type and developmental maturation, indicating a prominent role for distinct highly conserved intronic elements in forebrain inhibitory neuron differentiation. Two elements were hypomethylated in neural cells with higher MEIS1 expression, suggesting a role of enhancer demethylation in gene regulation. MEIS1 eQTLs showed a striking modular chromosomal distribution, with forebrain eQTLs clustering in intron 8/9. Clustered regularly interspersed short palindromic repeats interference targeting of individual elements in this region attenuated MEIS1 expression, revealing a complex regulatory interplay of distinct elements. In summary, we found that MEIS1 regulation is organized in a modular pattern. Disease-associated intronic regulatory elements control MEIS1 expression with cell type and maturation stage specificity, particularly in the inhibitory neuron lineage. The precise spatiotemporal activity of these elements likely contributes to the pathogenesis of insomnia and RLS.


Asunto(s)
Proteína 1 del Sitio de Integración Viral Ecotrópica Mieloide , Síndrome de las Piernas Inquietas , Trastornos del Inicio y del Mantenimiento del Sueño , Epigénesis Genética , Humanos , Intrones/genética , Proteína 1 del Sitio de Integración Viral Ecotrópica Mieloide/genética , Síndrome de las Piernas Inquietas/genética , Trastornos del Inicio y del Mantenimiento del Sueño/genética
2.
Ann Neurol ; 87(2): 184-193, 2020 02.
Artículo en Inglés | MEDLINE | ID: mdl-31788832

RESUMEN

OBJECTIVE: Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well-being and public health. Genetic risk loci have been identified, but the causatives genes at these loci are largely unknown, so that functional investigation and clinical translation of molecular research data are still inhibited. To identify putatively causative genes, we searched for highly significant mutational burden in candidate genes. METHODS: We analyzed 84 candidate genes in 4,649 patients and 4,982 controls by next generation sequencing using molecular inversion probes that targeted mainly coding regions. The burden of low-frequency and rare variants was assessed, and in addition, an algorithm (binomial performance deviation analysis) was established to estimate independently the sequence variation in the probe binding regions from the variation in sequencing depth. RESULTS: Highly significant results (considering the number of genes in the genome) of the conventional burden test and the binomial performance deviation analysis overlapped significantly. Fourteen genes were highly significant by one method and confirmed with Bonferroni-corrected significance by the other to show a differential burden of low-frequency and rare variants in restless legs syndrome. Nine of them (AAGAB, ATP2C1, CNTN4, COL6A6, CRBN, GLO1, NTNG1, STEAP4, VAV3) resided in the vicinity of known restless legs syndrome loci, whereas 5 (BBS7, CADM1, CREB5, NRG3, SUN1) have not previously been associated with restless legs syndrome. Burden test and binomial performance deviation analysis also converged significantly in fine-mapping potentially causative domains within these genes. INTERPRETATION: Differential burden with intragenic low-frequency variants reveals putatively causative genes in restless legs syndrome. ANN NEUROL 2020;87:184-193.


Asunto(s)
Análisis Mutacional de ADN , Predisposición Genética a la Enfermedad/genética , Síndrome de las Piernas Inquietas/genética , Estudios de Casos y Controles , Mapeo Cromosómico/estadística & datos numéricos , Femenino , Humanos , Masculino , Persona de Mediana Edad
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