Background and purpose Despite recent advances in neurogenetics that have facilitated the identification of a number of dystonia genes, many familial dystonia syndromes remain without known cause. The aim of the study was to identify the cause of autosomal dominant tremulous myoclonus‐dystonia in a UK kindred with affected individuals in three generations. Methods Known genetic causes of myoclonus‐dystonia were excluded. We combined clinical and electrophysiological phenotyping with whole‐exome sequencing and Sanger sequencing to identify candidate causal variants in a family with tremulous myoclonus‐dystonia. Results The core phenotype consisted of childhood‐onset dystonia predominantly affecting hands and neck, with a fast tremor with superimposed myoclonus and, in some individuals, subtle cerebellar signs. We identified a novel missense variant in potassium calcium‐activated channel subfamily N member 2 (KCNN2) [NM_021614:c.1112G>A:p.(Gly371Glu)], which was the only variant that we were able to identify as segregating with the phenotype over three generations. This variant, which is absent from the most recent version of gnomAD, was predicted to be deleterious by SIFT and PolyPhen‐2 and had an overall CADD score of 29.7. Conclusions KCNN2, a member of the KCNN family of potassium channel genes, is highly conserved across species and in humans is highly expressed in the brain, particularly the cerebellum. KCNN2 mutations have never been described as pathological in human disease, but are recognized abnormalities in two rodent models of fast, jerky tremor. Segregation, absence of the variant in the normal population and in‐silico prediction of a deleterious effect together with animal models compatible with the clinical phenotype are all in line with KCNN2 mutations being a plausible cause underlying myoclonus‐dystonia.

In just over a decade, advances in genome-wide association studies (GWAS) have offered an approach to stratify individuals based on genetic risk for disease. Using recent Alzheimer's disease (AD) GWAS results as the base data, we determined each individual's polygenic risk score (PRS) in the UK Biobank dataset. Using individuals within the extreme risk distribution, we performed a GWAS that is agnostic of AD phenotype and is instead based on known genetic risk for disease. To interpret the functions of the new risk factors, we conducted phenotype analyses, including a phenome-wide association study. We identified 246 loci surpassing the significance threshold of which 229 were not reported in the base AD GWAS. These include loci that showed suggestive levels of association in the base GWAS and loci not previously suspected to be associated with AD. Among these, there are loci, such as IL34 and KANSL1, that have since been shown to be associated with AD in recent studies. We also show highly significant genetic correlations with multiple health-related outcomes that provide insights into prodromal symptoms and comorbidities. This is the first study to utilize PRS as a phenotype-agnostic group classification in AD genetic studies. We identify potential new loci for AD and detail phenotypic analysis of these PRS extremes.

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.