Genomics of perivascular space burden unravels early mechanisms of cerebral small vessel disease.

Perivascular space (PVS) burden is an emerging, poorly understood, magnetic resonance imaging marker of cerebral small vessel disease, a leading cause of stroke and dementia. Genome-wide association studies in up to 40,095 participants (18 population-based cohorts, 66.3 ± 8.6 yr, 96.9% European ancestry) revealed 24 genome-wide significant PVS risk loci, mainly in the white matter. These were associated with white matter PVS already in young adults (N = 1,748; 22.1 ± 2.3 yr) and were enriched in early-onset leukodystrophy genes and genes expressed in fetal brain endothelial cells, suggesting early-life mechanisms. In total, 53% of white matter PVS risk loci showed nominally significant associations (27% after multiple-testing correction) in a Japanese population-based cohort (N = 2,862; 68.3 ± 5.3 yr). Mendelian randomization supported causal associations of high blood pressure with basal ganglia and hippocampal PVS, and of basal ganglia PVS and hippocampal PVS with stroke, accounting for blood pressure. Our findings provide insight into the biology of PVS and cerebral small vessel disease, pointing to pathways involving extracellular matrix, membrane transport and developmental processes, and the potential for genetically informed prioritization of drug targets.

Heterozygous PNPT1 Variants Cause Spinocerebellar Ataxia Type 25.

OBJECTIVE: Dominant spinocerebellar ataxias (SCA) are characterized by genetic heterogeneity. Some mapped and named loci remain without a causal gene identified. Here we applied next generation sequencing (NGS) to uncover the genetic etiology of the SCA25 locus. METHODS: Whole-exome and whole-genome sequencing were performed in families linked to SCA25, including the French family in which the SCA25 locus was originally mapped. Whole exome sequence data were interrogated in a cohort of 796 ataxia patients of unknown etiology. RESULTS: The SCA25 phenotype spans a slowly evolving sensory and cerebellar ataxia, in most cases attributed to ganglionopathy. A pathogenic variant causing exon skipping was identified in the gene encoding Polyribonucleotide Nucleotidyltransferase PNPase 1 (PNPT1) located in the SCA25 linkage interval. A second splice variant in PNPT1 was detected in a large Australian family with a dominant ataxia also mapping to SCA25. An additional nonsense variant was detected in an unrelated individual with ataxia. Both nonsense and splice heterozygous variants result in premature stop codons, all located in the S1-domain of PNPase. In addition, an elevated type I interferon response was observed in blood from all affected heterozygous carriers tested. PNPase notably prevents the abnormal accumulation of double-stranded mtRNAs in the mitochondria and leakage into the cytoplasm, associated with triggering a type I interferon response. INTERPRETATION: This study identifies PNPT1 as a new SCA gene, responsible for SCA25, and highlights biological links between alterations of mtRNA trafficking, interferonopathies and ataxia. ANN NEUROL 2022;92:122-137.

Common variants in Alzheimer's disease and risk stratification by polygenic risk scores.

Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease.

Pathogenic Variants in GPC4 Cause Keipert Syndrome.

Glypicans are a family of cell-surface heparan sulfate proteoglycans that regulate growth-factor signaling during development and are thought to play a role in the regulation of morphogenesis. Whole-exome sequencing of the Australian family that defined Keipert syndrome (nasodigitoacoustic syndrome) identified a hemizygous truncating variant in the gene encoding glypican 4 (GPC4). This variant, located in the final exon of GPC4, results in premature termination of the protein 51 amino acid residues prior to the stop codon, and in concomitant loss of functionally important N-linked glycosylation (Asn514) and glycosylphosphatidylinositol (GPI) anchor (Ser529) sites. We subsequently identified seven affected males from five additional kindreds with novel and predicted pathogenic variants in GPC4. Segregation analysis and X-inactivation studies in carrier females provided supportive evidence that the GPC4 variants caused the condition. Furthermore, functional studies of recombinant protein suggested that the truncated proteins p.Gln506∗ and p.Glu496∗ were less stable than the wild type. Clinical features of Keipert syndrome included a prominent forehead, a flat midface, hypertelorism, a broad nose, downturned corners of mouth, and digital abnormalities, whereas cognitive impairment and deafness were variable features. Studies of Gpc4 knockout mice showed evidence of the two primary features of Keipert syndrome: craniofacial abnormalities and digital abnormalities. Phylogenetic analysis demonstrated that GPC4 is most closely related to GPC6, which is associated with a bone dysplasia that has a phenotypic overlap with Keipert syndrome. Overall, we have shown that pathogenic variants in GPC4 cause a loss of function that results in Keipert syndrome, making GPC4 the third human glypican to be linked to a genetic syndrome.

Detecting Expansions of Tandem Repeats in Cohorts Sequenced with Short-Read Sequencing Data.

Repeat expansions cause more than 30 inherited disorders, predominantly neurogenetic. These can present with overlapping clinical phenotypes, making molecular diagnosis challenging. Single-gene or small-panel PCR-based methods can help to identify the precise genetic cause, but they can be slow and costly and often yield no result. Researchers are increasingly performing genomic analysis via whole-exome and whole-genome sequencing (WES and WGS) to diagnose genetic disorders. However, until recently, analysis protocols could not identify repeat expansions in these datasets. We developed exSTRa (expanded short tandem repeat algorithm), a method that uses either WES or WGS to identify repeat expansions. Performance of exSTRa was assessed in a simulation study. In addition, four retrospective cohorts of individuals with eleven different known repeat-expansion disorders were analyzed with exSTRa. We assessed results by comparing the findings to known disease status. Performance was also compared to three other analysis methods (ExpansionHunter, STRetch, and TREDPARSE), which were developed specifically for WGS data. Expansions in the assessed STR loci were successfully identified in WES and WGS datasets by all four methods with high specificity and sensitivity. Overall, exSTRa demonstrated more robust and superior performance for WES data than did the other three methods. We demonstrate that exSTRa can be effectively utilized as a screening tool for detecting repeat expansions in WES and WGS data, although the best performance would be produced by consensus calling, wherein at least two out of the four currently available screening methods call an expansion.

Recent advances in the detection of repeat expansions with short-read next-generation sequencing.

Short tandem repeats (STRs), also known as microsatellites, are commonly defined as consisting of tandemly repeated nucleotide motifs of 2-6 base pairs in length. STRs appear throughout the human genome, and about 239,000 are documented in the Simple Repeats Track available from the UCSC (University of California, Santa Cruz) genome browser. STRs vary in size, producing highly polymorphic markers commonly used as genetic markers. A small fraction of STRs (about 30 loci) have been associated with human disease whereby one or both alleles exceed an STR-specific threshold in size, leading to disease. Detection of repeat expansions is currently performed with polymerase chain reaction-based assays or with Southern blots for large expansions. The tests are expensive and time-consuming and are not always conclusive, leading to lengthy diagnostic journeys for patients, potentially including missed diagnoses. The advent of whole exome and whole genome sequencing has identified the genetic cause of many genetic disorders; however, analysis pipelines are focused primarily on the detection of short nucleotide variations and short insertions and deletions (indels). Until recently, repeat expansions, with the exception of the smallest expansion (SCA6), were not detectable in next-generation short-read sequencing datasets and would have been ignored in most analyses. In the last two years, four analysis methods with accompanying software (ExpansionHunter, exSTRa, STRetch, and TREDPARSE) have been released. Although a comprehensive comparative analysis of the performance of these methods across all known repeat expansions is still lacking, it is clear that these methods are a valuable addition to any existing analysis pipeline. Here, we detail how to assess short-read data for evidence of expansions, reviewing all four methods and outlining their strengths and weaknesses. Implementation of these methods should lead to increased diagnostic yield of repeat expansion disorders for known STR loci and has the potential to detect novel repeat expansions.