Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the ‘transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

We surveyed 16 subjects with the clinical diagnosis of Noonan Syndrome (NS1) from 12 families and their relevant family members for mutations in PTPN11/SHP2 using direct DNA sequencing. We found three different mutations among five families. Two unrelated subjects shared the same de novo missense substitution in exon 13 (S502T); an additional two unrelated families had a mutation in exon 3 (Y63C); and one subject had the amino acid substitution Y62D, also in exon 3. None of the three mutations were present in ethnically matched controls. In the mature protein model, the exon 3 mutants and the exon 13 mutant amino acids cluster at the interface between the N' SH2 domain and the phosphatase catalytic domain. Six of eight subjects with PTPN11/SHP2 mutations had pulmonary valve stenosis while no mutations were identified in those subjects (N = 4) with hypertrophic cardiomyopathy. An additional four subjects with possible Noonan syndrome were evaluated, but no mutations in PTPN11/SHP2 were identified. These results confirm that mutations in PTPN11/SHP2 underlie a common form of Noonan syndrome, and that the disease exhibits both allelic and locus heterogeneity. The observation of recurrent mutations supports the hypothesis that a special class of gain-of-function mutations in SHP2 give rise to Noonan syndrome.

Parkinson's disease (PD) is a genetically complex disorder. Multiple genes have been shown to contribute to the risk of PD, and currently 90 independent risk variants have been identified by genome-wide association studies. Thus far, a number of genes (including SNCA, LRRK2, and GBA) have been shown to contain variability across a spectrum of frequency and effect, from rare, highly penetrant variants to common risk alleles with small effect sizes.Variants in GBA, encoding the enzyme glucocerebrosidase, are associated with Lewy body diseases such as PD and Lewy body dementia (LBD). These variants, which reduce or abolish enzymatic activity, confer a spectrum of disease risk, from 1.4-to >10-fold. An outstanding question in the field is what other genetic factors that influence GBA-associated risk for disease, and whether these overlap with known PD risk variants.Using multiple, large case-control datasets, totalling 217,165 individuals (22,757 PD cases, 13,431 PD proxy cases, 622 LBD cases and 180,355 controls), we identified 1,772 PD cases, 711 proxy cases and 7,624 controls with a GBA variant (p.E326K, p.T369M or p.N370S). We performed a genome-wide association study and analysed the most recent PD-associated genetic risk score to detect genetic influences on GBA risk and age at onset. We attempted to replicate our findings in two independent datasets, including the personal genetics company 23andMe, Inc. and whole-genome sequencing data. Our analysis showed that the overall PD genetic risk score modifies risk for disease and decreases age at onset in carriers of GBA variants. Notably, this effect was consistent across all tested GBA risk variants. Dissecting this signal demonstrated that variants in close proximity to SNCA and CTSB (encoding cathepsin B) are the most significant contributors. Risk variants in the CTSB locus were identified to decrease mRNA expression of CTSB. Additional analyses suggest a possible genetic interaction between GBA and CTSB and GBA p.N370S neurons were shown to have decreased Cathepsin B expression compared to controls. These data provide a genetic basis for modification of GBA-associated PD risk and age at onset and demonstrate that variability at genes implicated in lysosomal function exerts the largest effect on GBA associated risk for disease. Further, these results have important implications for selection of GBA carriers for therapeutic interventions. 5

Background Previous studies reported various symptoms of Parkinson's disease (PD) associated with sex. Some were conflicting or confirmed in only one study. Objectives We examined sex associations to PD phenotypes cross‐sectionally and longitudinally in large‐scale data. Methods We tested 40 clinical phenotypes, using longitudinal, clinic‐based patient cohorts, consisting of 5946 patients, with a median follow‐up of 3.1 years. For continuous outcomes, we used linear regressions at baseline to test sex‐associated differences in presentation, and linear mixed‐effects models to test sex‐associated differences in progression. For binomial outcomes, we used logistic regression models at baseline and Cox regression models for survival analyses. We adjusted for age, disease duration, and medication use. In the secondary analyses, data from 17 719 PD patients and 7588 non‐PD participants from an online‐only, self‐assessment PD cohort were cross‐sectionally evaluated to determine whether the sex‐associated differences identified in the primary analyses were consistent and unique to PD. Results Female PD patients had a higher risk of developing dyskinesia early during the follow‐up period, with a slower progression in activities of daily living difficulties, and a lower risk of developing cognitive impairments compared with male patients. The findings in the longitudinal, clinic‐based cohorts were mostly consistent with the results of the online‐only cohort. Conclusions We observed sex‐associated contributions to PD heterogeneity. These results highlight the necessity of future research to determine the underlying mechanisms and importance of personalized clinical management. © 2020 International Parkinson and Movement Disorder Society