Javier Simón-Sánchez

The genetics of dystonia have been extensively investigated in population-based and multicenter cohorts. In this study, we analyzed a consecutively recruited, single-center German dystonia cohort using whole-exome sequencing ( n = 153 affected individuals [ n = 152 index cases from 152 dystonia families], n = 10 unaffected family members). Pathogenic or likely pathogenic variants were identified in established ( n = 7) and less-established ( n = 4) dystonia-associated genes, resulting in a diagnostic yield of 7.2% (11/152); all variants were heterozygous. Consistent with previous European studies, earlier age at onset (≤ 40 years; p value = 0.0218) was significantly associated with increased diagnostic yield and demonstrated acceptable predictive value (AUC = 0.76). This study (1) underscores the importance of both shared features—such as clinical characteristics associated with diagnostic yield—and distinct genetic features, including a relatively lower diagnostic rate and differences in the composition of implicated genes across cohort designs, and (2) suggests that exome-based testing may identify clinically relevant variants beyond the classic dystonia genes in selected patients undergoing diagnostic evaluation.

Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson’s disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes—GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C—also showed evidence consistent with genetic replication. By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies.

Introduction: Mutations in the TANK‐binding kinase 1 (TBK1) gene have recently been shown to cause frontotemporal dementia (FTD). However, the phenotype of TBK1‐associated FTD is currently unclear.Methods: We performed a single case longitudinal study of a patient who was subsequently found to have a novel A705fs mutation in the TBK1 gene. He was assessed annually over a 7‐year period with a series of clinical, cognitive, and magnetic resonance imaging assessments. His brain underwent pathological examination at postmortem.Results: The patient presented at the age of 64 years with an 18‐month history of personality change including increased rigidity and obsessiveness, apathy, loss of empathy, and development of a sweet tooth. His mother had developed progressive behavioral and cognitive impairment from the age of 57 years. Neuropsychometry revealed intact cognition at first assessment. Magnetic resonance imaging showed focal right temporal lobe atrophy. Over the next few years his behavioral problems progressed and he developed cognitive impairment, initially with anomia and prosopagnosia. Neurological examination remained normal throughout without any features of motor neurone disease. He died at the age of 72 years and postmortem showed TDP‐43 type A pathology but with an unusual novel feature of numerous TAR DNA‐binding protein 43 (TDP‐43)–positive neuritic structures at the cerebral cortex/subcortical white matter junction. There was also associated argyrophilic grain disease not previously reported in other TBK1 mutation cases.Discussion: TBK1‐associated FTD can be associated with right temporal variant FTD with progressive behavioral change and relatively intact cognition initially. The case further highlights the benefits of next‐generation sequencing technologies in the diagnosis of neurodegenerative disorders and the importance of detailed neuropathologic analysis.

Expression quantitative trait loci (eQTL) analysis is a powerful method to detect correlations between gene expression and genomic variants and is widely used to interpret the biological mechanism underlying identified genome wide association studies (GWAS) risk loci. Numerous eQTL studies have been performed on different cell types and tissues of which the majority has been based on microarray technology. We present here an eQTL analysis based on cap analysis gene expression sequencing (CAGEseq) data created from human postmortem frontal lobe tissue combined with genotypes obtained through genotyping arrays, exome sequencing, and CAGEseq. Using CAGEseq as an expression profiling technique combined with these different genotyping techniques allows measurement of the molecular effect of variants on individual transcription start sites and increases the resolution of eQTL analysis by also including the non-annotated parts of the genome. We identified 2410 eQTLs and show that non-coding transcripts are more likely to contain an eQTL than coding transcripts, in particular antisense transcripts. We provide evidence for how previously identified GWAS loci for schizophrenia (NRGN), Parkinson’s disease, and Alzheimer’s disease (PARK16 and MAPT loci) could increase the risk for disease at a molecular level. Furthermore, we demonstrate that CAGEseq improves eQTL analysis because variants obtained from CAGEseq are highly enriched for having a functional effect and thus are an efficient method towards the identification of causal variants. Our data contain both coding and non-coding transcripts and has the added value that we have identified eQTLs for variants directly adjacent to TSS. Future eQTL studies would benefit from combining CAGEseq with RNA sequencing for a more complete interpretation of the transcriptome and increased understanding of eQTL signals.