Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD)1,2. These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low frequency coding variants with large effects on LOAD risk, we performed whole exome-sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large case-control datasets. A rare variant in PLD3 (phospholipase-D family, member 3, rs145999145; V232M) segregated with disease status in two independent families and doubled risk for AD in seven independent case-control series (V232M meta-analysis; OR= 2.10, CI=1.47-2.99; p= 2.93×10-5, 11,354 cases and controls of European-descent). Gene-based burden analyses in 4,387 cases and controls of European-descent and 302 African American cases and controls, with complete sequence data for PLD3, indicate that several variants in this gene increase risk for AD in both populations (EA: OR= 2.75, CI=2.05-3.68; p=1.44×10-11, AA: OR= 5.48, CI=1.77-16.92; p=1.40×10-3). PLD3 is highly expressed in brain regions vulnerable to AD pathology, including hippocampus and cortex, and is expressed at lower levels in neurons from AD brains compared to control brains (p=8.10×10-10). Over-expression of PLD3 leads to a significant decrease in intracellular APP and extracellular Aβ42 and Aβ40, while knock-down of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a two-fold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may be used to identify rare variants with large effects on risk for disease or other complex traits.

Summary Studies of long-lived individuals have revealed few genetic mechanisms for protection against age-associated disease. Therefore, we pursued genome sequencing of a related phenotype – healthy aging – to understand the genetics of disease-free aging without medical intervention. In contrast with studies of exceptional longevity, usually focused on centenarians, healthy aging is not associated with known longevity variants but is associated with reduced genetic susceptibility to Alzheimer and coronary artery disease. Additionally, healthy aging is not associated with a decreased rate of rare pathogenic variants, potentially indicating the presence of disease-resistance factors. In keeping with this possibility, we identify suggestive common and rare variant genetic associations implying that protection against cognitive decline is a genetic component of healthy aging. These findings, based on a relatively small cohort, require independent replication. Overall, our results suggest healthy aging is an overlapping but distinct phenotype from exceptional longevity that may be enriched with disease-protective genetic factors.

The feasibility of using mobile health applications to conduct observational clinical studies requires rigorous validation. Here, we report initial findings from the Asthma Mobile Health Study, a research study, including recruitment, consent, and enrollment, conducted entirely remotely by smartphone. We achieved secure bidirectional data flow between investigators and 7,593 participants from across the United States, including many with severe asthma. Our platform enabled prospective collection of longitudinal, multidimensional data (e.g., surveys, devices, geolocation, and air quality) in a subset of users over the 6-month study period. Consistent trending and correlation of interrelated variables support the quality of data obtained via this method. We detected increased reporting of asthma symptoms in regions affected by heat, pollen, and wildfires. Potential challenges with this technology include selection bias, low retention rates, reporting bias, and data security. These issues require attention to realize the full potential of mobile platforms in research and patient care.

Objective To identify the cause of childhood onset involuntary paroxysmal choreiform and dystonic movements in 2 unrelated sporadic cases and to investigate the functional effect of missense mutations in adenylyl cyclase 5 (ADCY5) in sporadic and inherited cases of autosomal dominant familial dyskinesia with facial myokymia (FDFM). Methods Whole exome sequencing was performed on 2 parent–child trios. The effect of mutations in ADCY5 was studied by measurement of cyclic adenosine monophosphate (cAMP) accumulation under stimulatory and inhibitory conditions. Results The same de novo mutation (c.1252C>T, p.R418W) in ADCY5 was found in both studied cases. An inherited missense mutation (c.2176G>A, p.A726T) in ADCY5 was previously reported in a family with FDFM. The significant phenotypic overlap with FDFM was recognized in both cases only after discovery of the molecular link. The inherited mutation in the FDFM family and the recurrent de novo mutation affect residues in different protein domains, the first cytoplasmic domain and the first membrane-spanning domain, respectively. Functional studies revealed a statistically significant increase in β-receptor agonist-stimulated intracellular cAMP consistent with an increase in adenylyl cyclase activity for both mutants relative to wild-type protein, indicative of a gain-of-function effect. Interpretation FDFM is likely caused by gain-of-function mutations in different domains of ADCY5—the first definitive link between adenylyl cyclase mutation and human disease. We have illustrated the power of hypothesis-free exome sequencing in establishing diagnoses in rare disorders with complex and variable phenotype. Mutations in ADCY5 should be considered in patients with undiagnosed complex movement disorders even in the absence of a family history.