Common variants in the microglia-specific MS4A gene cluster modify risk for late-onset Alzheimer’s disease and modulate extracellular soluble TREM2.

Background— Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is an inherited disorder typically caused by mutations in components of the cardiac desmosome. The prevalence and significance of desmosome mutations among patients with ARVD/C in North America have not been described previously. We report comprehensive desmosome genetic analysis for 100 North Americans with clinically confirmed or suspected ARVD/C. Methods and Results— In 82 individuals with ARVD/C and 18 people with suspected ARVD/C, DNA sequence analysis was performed on PKP2, DSG2, DSP, DSC2 , and JUP. In those with ARVD/C, 52% harbored a desmosome mutation. A majority of these mutations occurred in PKP2 . Notably, 3 of the individuals studied have a mutation in more than 1 gene. Patients with a desmosome mutation were more likely to have experienced ventricular tachycardia (73% versus 44%), and they presented at a younger age (33 versus 41 years) compared with those without a desmosome mutation. Men with ARVD/C were more likely than women to carry a desmosome mutation (63% versus 38%). A mutation was identified in 5 of 18 patients (28%) with suspected ARVD. In this smaller subgroup, there were no significant phenotypic differences identified between individuals with a desmosome mutation compared with those without a mutation. Conclusions— Our study shows that in 52% of North Americans with ARVD/C a mutation in one of the cardiac desmosome genes can be identified. Compared with those without a desmosome gene mutation, individuals with a desmosome gene mutation had earlier-onset ARVD/C and were more likely to have ventricular tachycardia.

Alzheimer’s disease (AD) is the most common form of dementia. This neurodegenerative disorder is associated with neuronal death and gliosis heavily impacting the cerebral cortex. AD has a substantial but heterogeneous genetic component, presenting both Mendelian and complex genetic architectures. Using bulk RNA-seq from the parietal lobes and deconvolution methods, we previously reported that brains exhibiting different AD genetic architecture exhibit different cellular proportions. Here, we sought to directly investigate AD brain changes in cell proportion and gene expression using single-cell resolution. We generated unsorted single-nuclei RNA sequencing data from brain tissue. We leveraged the tissue donated from a carrier of a Mendelian genetic mutation, PSEN1 p.A79V, and two family members who suffer from sporadic AD, but do not carry any autosomal mutations. We evaluated alternative alignment approaches to maximize the titer of reads, genes, and cells with high quality. In addition, we employed distinct clustering strategies to determine the best approach to identify cell clusters that reveal neuronal and glial cell types and avoid artifacts such as sample and batch effects. We propose an approach to cluster cells that reduces biases and enable further analyses. We identified distinct types of neurons, both excitatory and inhibitory, and glial cells, including astrocytes, oligodendrocytes, and microglia, among others. In particular, we identified a reduced proportion of excitatory neurons in the Mendelian mutation carrier, but a similar distribution of inhibitory neurons. Furthermore, we investigated whether single-nuclei RNA-seq from the human brains recapitulate the expression profile of disease-associated microglia (DAM) discovered in mouse models. We also determined that when analyzing human single-nuclei data, it is critical to control for biases introduced by donor-specific expression profiles. We propose a collection of best practices to generate a highly detailed molecular cell atlas of highly informative frozen tissue stored in brain banks. Importantly, we have developed a new web application to make this unique single-nuclei molecular atlas publicly available.

Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarker for reliable detection of Alzheimer’s disease (AD) pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-β (Aβ)-PET, tau-PET, and cognition as outcomes, and benchmarked them against cerebrospinal fluid (CSF) biomarker tests. Samples from 998 individuals (mean[range] age 68.5[20.0-92.5], 53% female) from the Swedish BioFINDER-2 cohort, including both cognitively unimpaired and cognitively impaired individuals, were analyzed. Plasma p-tau217 was measured with mass spectrometry (MS) assays (the ratio between phosphorylated and non-phosphorylated [%p-tau217_WashU] and p-tau217_WashU) as well as with immunoassays (p-tau217_Lilly, p-tau217_Janssen, p-tau217_ALZpath). CSF biomarkers included p-tau217_Lilly, the FDA-approved p-tau181/Aβ42_Elecsys, and p-tau181_Elecsys. All plasma p-tau217 tests exhibited a high ability to detect abnormal Aβ-PET (AUC range: 0.91-0.96) and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217_WashU had the highest performance, with significantly higher AUCs than all the immunoassays (P_diff<0.007). For detecting Aβ-PET status, %p-tau217_WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 91% (immunoassays: 84-87%), and a specificity of 94% (immunoassays: 85-89%). Among immunoassays, p-tau217_Lilly and plasma p-tau217_ALZpath had higher AUCs than plasma p-tau217_Janssen for Aβ-PET status (P_diff<0.006), and p-tau217_Lilly outperformed plasma p-tau217_ALZpath for tau-PET status (P_diff=0.025). Plasma %p-tau217_WashU exhibited stronger associations with all PET load outcomes compared to immunoassays; baseline Aβ-PET load (R²: 0.72; immunoassays: 0.47-0.58; P_diff<0.001), baseline tau-PET load (R²: 0.51; immunoassays: 0.38-0.45; P_diff<0.001), longitudinal Aβ-PET load (R²: 0.53; immunoassays: 0.31-0.38; P_diff<0.001) and longitudinal tau-PET load (R²: 0.50; immunoassays: 0.35-0.43; P_diff<0.014). Among immunoassays, plasma p-tau217_Lilly was more associated with Aβ-PET load than plasma p-tau217_Janssen (P_diff<0.020) and with tau-PET load than both plasma p-tau217_Janssen and plasma p-tau217_ALZpath (all P_diff<0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination[MMSE]) than all immunoassays (R² %p-tau217_WashU: 0.33; immunoassays: 0.27-0.30; P_diff<0.024). The main results were replicated in an external cohort from Washington University in St Louis (n =219). Finally, p-tau217_NULISA showed similar performance to other immunoassays in subsets of both cohorts. In summary, both MS- and immunoassay-based p-tau217 tests generally perform well in identifying Aβ-PET, tau-PET, and cognitive abnormalities, but %p-tau217_WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for AD pathology, while some immunoassays might be better suited as triage tests where positive results are confirmed with a second test, which needs to be determined by future reviews incorporating results from multiple cohorts.