Showing papers by "Jared C. Roach published in 2022"

Rare variants implicate NMDA receptor signaling and cerebellar gene networks in risk for bipolar disorder

Abstract: Bipolar disorder is an often-severe mental health condition characterized by alternation between extreme mood states of mania and depression. Despite strong heritability and the recent identification of 64 common variant risk loci of small effect, pathophysiological mechanisms remain unknown. Here, we analyzed genome sequences from 41 multiply-affected pedigrees and identified variants in 741 genes with nominally significant linkage or association with bipolar disorder. These 741 genes overlapped known risk genes for neurodevelopmental disorders and clustered within gene networks enriched for synaptic and nuclear functions. The top variant in this analysis – prioritized by statistical association, predicted deleteriousness, and network centrality – was a missense variant in the gene encoding D-amino acid oxidase (DAOG131V). Heterologous expression of DAOG131V in human cells resulted in decreased DAO protein abundance and enzymatic activity. In a knock-in mouse model of DAOG131, DaoG130V/+, we similarly found decreased DAO protein abundance in hindbrain regions, as well as enhanced stress susceptibility and blunted behavioral responses to pharmacological inhibition of N-methyl-D-aspartate receptors (NMDARs). RNA sequencing of cerebellar tissue revealed that DaoG130V resulted in decreased expression of two gene networks that are enriched for synaptic functions and for genes expressed, respectively, in Purkinje neurons or granule neurons. These gene networks were also down-regulated in the cerebellum of patients with bipolar disorder compared to healthy controls and were enriched for additional rare variants associated with bipolar disorder risk. These findings implicate dysregulation of NMDAR signaling and of gene expression in cerebellar neurons in bipolar disorder pathophysiology and provide insight into its genetic architecture.

The Coaching for Cognition in Alzheimer's (COCOA) trial: Study design

Abstract: Comprehensive treatment of Alzheimer's disease (AD) requires not only pharmacologic treatment but also management of existing medical conditions and lifestyle modifications including diet, cognitive training, and exercise. We present the design and methodology for the Coaching for Cognition in Alzheimer's (COCOA) trial. AD and other dementias result from the interplay of multiple interacting dysfunctional biological systems. Monotherapies have had limited success. More interventional studies are needed to test the effectiveness of multimodal multi‐domain therapies for dementia prevention and treatment. Multimodal therapies use multiple interventions to address multiple systemic causes and potentiators of cognitive decline and functional loss; they can be personalized, as different sets of etiologies and systems responsive to therapy may be present in different individuals. COCOA is designed to test the hypothesis that coached multimodal interventions beneficially alter the trajectory of cognitive decline for individuals on the spectrum of AD and related dementias (ADRD). COCOA is a two‐arm prospective randomized controlled trial (RCT). COCOA collects psychometric, clinical, lifestyle, genomic, proteomic, metabolomic, and microbiome data at multiple timepoints across 2 years for each participant. These data enable systems biology analyses. One arm receives standard of care and generic healthy aging recommendations. The other arm receives standard of care and personalized data‐driven remote coaching. The primary outcome measure is the Memory Performance Index (MPI), a measure of cognition. The MPI is a summary statistic of the MCI Screen (MCIS). Secondary outcome measures include the Functional Assessment Staging Test (FAST), a measure of function. COCOA began enrollment in January 2018. We hypothesize that multimodal interventions will ameliorate cognitive decline and that data‐driven health coaching will increase compliance, assist in personalizing multimodal interventions, and improve outcomes for patients, particularly for those in the early stages of the AD spectrum.

Reinfection with SARS-CoV-2 and Waning Humoral Immunity: A Case Report

Abstract: Recovery from COVID-19 is associated with production of anti-SARS-CoV-2 antibodies, but it is uncertain whether these confer immunity. We describe viral RNA shedding duration in hospitalized patients and identify patients with recurrent shedding. We sequenced viruses from two distinct episodes of symptomatic COVID-19 separated by 144 days in a single patient, to conclusively describe reinfection with a different strain harboring the spike variant D614G. This case of reinfection was one of the first cases of reinfection reported in 2020. With antibody, B cell and T cell analytics, we show correlates of adaptive immunity at reinfection, including a differential response in neutralizing antibodies to a D614G pseudovirus. Finally, we discuss implications for vaccine programs and begin to define benchmarks for protection against reinfection from SARS-CoV-2.

Dense data enables 21st century clinical trials

Abstract: Alzheimer’s disease (AD) is one of the most significant challenges of our time. We need a diverse research portfolio. We cannot afford to shut down avenues of research. A century of domination by the amyloid hypothesis stifled AD research. We cannot again afford last century’s opportunity cost. Health care delayed is health care denied. Trials take years. Trials should be done in parallel where possible. If we were to test all possible single-mode interventions before testing any other hypotheses, it would take decades—if not centuries. Given the high expected return on AD research investment, we do not advocate redistributing money among AD trials as a zero-sum game; rather, we should increase funding for all AD research. If there were a need to redistribute global AD funding, we note that pharmaceutical companies may spend billions of dollars bringing to market products that are less validated and less effective than multimodal therapy or its components. A recommendation to reallocate funding formultimodal trials that are several orders of magnitude less expensive than pharmaceutical trials seemsmistargeted. At the Institute for SystemsBiology (ISB), we aim to change the epistemological nature of clinical studies.1 Most 20th-century clinical trials were primarily built on two epistemological pillars: significance and effect size. There are limits to the knowledge that is reachable from standingonly on these twopillars. Someknowledge—typically themost satisfying—canonlybegained frommechanistic or causal insights. Integrated learning leveraging multiple diverse large datasets is increasingly important to many fields, including commerce, and is becoming a major driver of biomedical knowledge and breakthroughs. It is time formost clinical studies to generate the dense data necessary to power such learning. Contributing to global knowledge should now be a factor in clinical trial design. Commitment to generating globally useful datasets should be part of updated trial-design guidelines. Our recommendations are not restricted to AD research—they can be applied to all complex diseases. With sufficiently deep data, much can be learned by integrating data across multiple domains. Multimodal AD therapies are in wide use; Americans are spending money and opportunity cost to pursue them. There is a demand from the members of our democracy to fund research for multimodal therapies. It is urgent to provide these citizens and their healthcare providers with science. Prospective randomized controlled trials (RCTs) provide the best form of evidence. We have an obligation to return research value to the people that support us.