Longitudinal associations of blood phosphorylated tau181 and neurofilament light chain with neurodegeneration in Alzheimer disease
1. Increases in tau phosphorylated at threonine 181 (p-tau181) in blood plasma were associated with progressive, longitudinal neurodegeneration.
2. Findings of p-tau181 were consistent with brain regions characteristic of Alzheimer’s disease, though only among participants with elevated brain amyloid-β.
Evidence Rating Level: 2 (Good)
Alzheimer’s disease (AD) is the leading form of dementia, characterized by the brain’s accumulation of amyloid-β plaques and neurofibrillary tangles of hyperphosphorylated tau. Converging evidence suggests that plasma phosphorylated tau at threonine 181 (p-tau181) is an AD pathology biomarker that can be easily accessed. The ability of p-tau181 to monitor disease progression, however, is less clear. This longitudinal cohort study aimed to study longitudinal p-tau181 measures for assessing the progression of degenerative processes and cognitive decline in AD compared to neurofilament light chain (NfL), a disease-nonspecific marker of neuronal injury. Data between February 2007 and June 2016 from the Alzheimer’s Disease Neuroimaging Initiative was used. Further, follow-up blooding sampling was performed for up to eight years and plasma p-tau181 measurements were performed in 2020. Participants were eligible if they had available plasma p-tau181 and NfL measurements as well as at least one FDG PET or MRI scan at the same study visit. Significant neurologic disorders other than AD, infarction, infection, and multiple lacunes resulted in exclusion. A total of 1,113 (M [SD] age = 74.0 [7.6] years, 46.1% female, 89.1% non-Hispanic White) were included in the final dataset. Within the sample, 34.0% were cognitively unimpaired (CU) and 66.0% were cognitively impaired (CImp). The CImp group included mild cognitive impairment (73.1%) and AD dementia (26.9%). Plasma p-tau181 changes over time were associated with cognitive decline (CU: r = -0.24, p<.001; CImp: r = 0.34, p<.001). Prospective decreases in glucose metabolism (CU: r = -0.05, p = 0.48); CImp: r = -0.27, p<.001) and gray matter volume (CU: r = -0.19, p<.001; CImp: r = -0.31, p<.001) were also associated with cognitive decline in AD-related brain regions. However, these associations were only evident in individuals with amyloid-β aggregation. Both plasma p-tau181 and NfL were found to be independently associated with neurodegeneration and cognitive decline in AD-specific brain regions, but NfL was also associated with other brain regions in amyloid-β-negative individuals. Approximately 25% to 45% of plasma p-tau181 outcomes on cognitive measures were mediated by the imaging-derived neurodegeneration markers, such that plasma p-tau181 may be linked to cognition independent of these markers. A major limitation to consider is the lack of racial/ethnic diversity among the sample studied, which may be related to a lack of neuroimaging data available among these groups in the national dataset. Overall, this study suggests that p-tau181 is an easily accessible biomarker for AD that may help predict and monitor progression of cognitive decline and neurodegeneration, specifically for individuals with AD.
Gaps in evidence-based therapy use in insured patients in the United States with type 2 diabetes mellitus and atherosclerotic cardiovascular disease
1. Significant gaps were found in the use of evidence-based therapies in insured patients with atherosclerotic cardiovascular disease and type 2 diabetes mellitus.
Evidence Rating Level: 2 (Good)
Prevalence of atherosclerotic cardiovascular disease (ASCVD) in patients with type 2 diabetes mellitus (T2DM) is twice as high as those without T2DM, resulting in worse health outcomes and premature death. Several classes of medications have proven efficacy for individuals with ASCVD and T2DM, such as angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), high-intensity statins, sodium glucose cotransporter-2 inhibitors (SGLT-2is), and glucagon-like peptide-1 receptor agonists (GLP-1RAs). However, evidence suggests that these medications are underutilized with this population. A total of 699,380 patients with T2DM insured with Anthem on April 30, 2018 and enrolled for a period of 12 months thereafter were included in this cohort study. Among these, 155,958 had evidence of ASCVD and were greater than 18 years of age without chronic kidney disease stage 4 or 5. The primary outcome was the proportion of patients with prescription claims for each of the three classes of evidence-based therapy on, or covering, the index date ±30 days: ACEI/ARB (or angiotensin receptor-neprilysin inhibitor), high-intensity statin (atorvastatin 40-80mg or rosuvastatin 20-40mg), and SGLT-2i or GLP-1RA. Of the patients in this sample, 24.7% were using a high-intensity statin, 53.1% were using an ACEI/ARB, and 9.9% were using a SGLT-2i or GLP-1RA. Only 2.7% of the population were covered by prescriptions for all three therapies; 37.4% were on none of these therapies. Over the course of 12 months, only 18% visited an endocrinologist while 70.6% had visited a cardiologist. Lastly, the potential benefit of achieving 100% adoption of the three therapies was simulated using pooled treatment estimates from clinical trials. Increasing the use of these evidence-based therapies to 100% over three years of treatment could reduce 4,546 major atherosclerotic cardiovascular events, such as stroke, myocardial infarction, or cardiovascular death, in eligible but untreated patients. Overall, this study found significant deviations from contemporary use of the three evidence-based therapies in insured patients with T2DM and ASCVD.
Potential impact of individual exposure histories to endemic human coronaviruses on age-dependent severity of COVID-19
1. Based on mathematical modeling, cross-reactivity between SARS-CoV-2 and other endemic human coronaviruses may explain variations in disease severity across age groups.
Evidence Rating Level: 3 (Average)
SARS-CoV-2 is the seventh known coronavirus to infect humans. Its resultant coronavirus disease 2019 (COVID-19) has resulted in over 400,000 deaths in the United States. With significant variations in symptom severity, based on a wide range of risk factors such as age and medical history, it is important to understand how cross-reactivity between SARS-CoV-2 and other endemic human coronaviruses (eHCoVs) impacts symptom severity. This study aimed to investigate the role of cross-reactivity induced by eHCoVs on age-specific COVID-19 severity in a mathematical model of eHCoV and SARS-CoV-2 transmission. An individual-based model was utilized, calibrated based on known eHCoV dynamics, to track individual eHCoV exposure histories. Emergent dynamics of SARS-CoV-2 and risk of hospitalization upon infection were also modeled. Epidemiological parameters characterizing SARS-CoV-2 and eHCoVs were informed, when feasible, by extant literature. Susceptibility to reinfection was set to match empirical estimates of age at first eHCoV infection, thus yielding a realistic force of infection for eHCoVs. Assumptions were compatible with studies on kinetics of antibody responses after both eHCoVs and SARS-CoV-2 infections. It was found that primary exposure with any eHCoV confers temporary cross-protection against severe SARS-CoV-2 infection. However, lifelong re-exposure to the same eHCoV diminishes cross-protection over time, increasing the risk of severe disease. This proposed mechanism was found to explain observable age patterns of COVID-19 hospitalizations in EU/EEA countries and the UK. Also under this model, variations in healthcare capacity and testing efforts are compatible with country-specific differences in hospital rates. Overall, the proposed modeling offers “proof of possibility” for certain epidemiological and biological mechanisms that may be driving COVID-19 variations across age groups. Future studies will need to focus on cross-reactivity to eHCoVs in the context of SARS-CoV-2.
Pharmacotherapy in the management of anxiety and pain during acute coronary syndromes and the risk of developing symptoms of posttraumatic stress disorder
1. Patients with acute coronary symptoms exposed to benzodiazepines had four-fold relative risk of developing posttraumatic stress disorder, adjusting for symptoms of acute stress disorder.
Evidence Rating Level: 2 (Good)
Morphine and benzodiazepines are often provided during acute coronary syndromes (ACSs) for pain and anxiety, with beta-blockers also serving to reduce pain. However, benzodiazepines are known to increase the risk of posttraumatic stress symptoms (PTSS) during other traumas, suggesting that they may act similarly in ACS. This retrospective cohort study recruited 154 participants (M [SD] age = 58.7 [10.9] years, 15.6% female) from the Myocardial Infarction-Stress Prevention Intervention (MI-SPRINT) randomized controlled trial with a verified ACS, extracting baseline demographic, clinical, and psychological variables from patient records. Posttraumatic stress symptoms were assessed via the Clinician-Administered PTSD Scale (CAPS). PTSS were assessed three months following ACS. Approximately 37.7% of patients were exposed to benzodiazepines during ACS, while 72.1% were exposed to morphine and 88.3% to beta-blockers. Only 7.1% were provided antidepressant medication. Of the 154 participants, 11.7% (18) participants developed PTSD. Benzodiazepine use was significantly associated with CAPS total severity score after adjusting for all covariates (unstandardized coefficient B [SE] = 0.589 [0.274]; partial r = 0.18, p = 0.032). Benzodiazepine use was also associated with the re-experiencing score of the CAPS, which includes nightmares (B [SD] = 0.433 [0.217]; partial r = 0.17, p = 0.047). Those who were exposed to benzodiazepines demonstrated nearly four-times greater relative risk of developing PTSD, adjusting for symptoms of acute stress disorder (OR = 3.75, 95% CI 1.31 to 10.77). No predictive value was yielded from morphine, beta-blockers, or antidepressants. Overall, this study suggests that benzodiazepines, while effective in the short-term, may increase the risk of developing PTSD and related symptoms in those with ACS.
Longitudinal trends in childhood insulin levels and body mass index and associations with risks of psychosis and depression in young adults
1. Persistently high fasting insulin levels were associated with psychosis and psychotic disorder later in life.
2. Major increases in body mass index during puberty were associated with increased risk of depression later in life, but not psychosis.
Evidence Rating Level: 2 (Good)
Cardiometabolic disorders often co-occur with schizophrenia and depression, which exacerbates declines in functional abilities, quality of life, and overall health outcomes. While some of these disorders are often attributed, in part, to lifestyle factors, there is evidence to suggest that first-episode psychosis may arise from altered glucose-insulin homeostasis in young, drug-naïve patients. This cohort study using repeated-measure data from the Avon Longitudinal Study of Parents and Children, a population-representative British dataset, chose individuals from ages 1 to 24 years with body mass index (BMI) and fasting insulin (FI) information available across that time period. FI levels were measured at 9, 15, 18, and 24 years while BMI was measured at 1, 2, 3, 4, 7, 9, 10, 11, 12, 15, 18, and 24 years. A total of 5,790 participants (54.1% female) had sufficient FL level data and 10,463 (51.0% female) had sufficient BMI data. Five distinct trajectories for BMI and three distinct trajectories for FI levels were found, which were evident by mid-childhood. Puberty-onset, major increases in BMI were associated with depression (adjusted OR = 4.46, 95% CI 2.38 to 9.87) but not psychosis (adjusted OR = 1.98, 95% CI 0.56 to 7.79). The trajectory of persistently high Fl levels was associated with a psychosis at-risk mental stated (adjusted OR = 5.01, 95% CI 1.76 to 13.19) and psychotic disorder (adjusted OR = 3.22, 95% CI 1.11 to 9.90) but not depression (adjusted OR = 1.38, 95% CI 0.75 to 2.54). Overall, this study suggests that cardiometabolic comorbidities of psychosis and depression have distinct, early-life origins. Altered insulin sensitivity may be a risk factor for psychosis while major increases in BMI may be a risk factor for depression later in life. This highlights the importance of comprehensive care among individuals with these co-occurring conditions, along with monitoring of potential psychiatric symptoms over time.
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