ELAVL4, splicing, and glutamatergic dysfunction precede neuron loss in MAPT mutation cerebral organoids.

Frontotemporal dementia (FTD) because of MAPT mutation causes pathological accumulation of tau and glutamatergic cortical neuronal death by unknown mechanisms. We used human induced pluripotent stem cell (iPSC)-derived cerebral organoids expressing tau-V337M and isogenic corrected controls to discover early alterations because of the mutation that precede neurodegeneration. At 2 months, mutant organoids show upregulated expression of MAPT, glutamatergic signaling pathways, and regulators, including the RNA-binding protein ELAVL4, and increased stress granules. Over the following 4 months, mutant organoids accumulate splicing changes, disruption of autophagy function, and build-up of tau and P-tau-S396. By 6 months, tau-V337M organoids show specific loss of glutamatergic neurons as seen in individuals with FTD. Mutant neurons are susceptible to glutamate toxicity, which can be rescued pharmacologically by the PIKFYVE kinase inhibitor apilimod. Our results demonstrate a sequence of events that precede neurodegeneration, revealing molecular pathways associated with glutamate signaling as potential targets for therapeutic intervention in FTD.

Systematic characterization of mutations altering protein degradation in human cancers.

The ubiquitin-proteasome system (UPS) is the primary route for selective protein degradation in human cells. The UPS is an attractive target for novel cancer therapies, but the precise UPS genes and substrates important for cancer growth are incompletely understood. Leveraging multi-omics data across more than 9,000 human tumors and 33 cancer types, we found that over 19% of all cancer driver genes affect UPS function. We implicate transcription factors as important substrates and show that c-Myc stability is modulated by CUL3. Moreover, we developed a deep learning model (deepDegron) to identify mutations that result in degron loss and experimentally validated the prediction that gain-of-function truncating mutations in GATA3 and PPM1D result in increased protein stability. Last, we identified UPS driver genes associated with prognosis and the tumor microenvironment. This study demonstrates the important role of UPS dysregulation in human cancer and underscores the potential therapeutic utility of targeting the UPS.

Hemodynamic regulation allows stable growth of microvascular networks.

How do vessels find optimal radii? Capillaries are known to adapt their radii to maintain the shear stress of blood flow at the vessel wall at a set point, yet models of adaptation purely based on average shear stress have not been able to produce complex loopy networks that resemble real microvascular systems. For narrow vessels where red blood cells travel in a single file, the shear stress on vessel endothelium peaks sharply when a red blood cell passes through. We show that stable shear-stress-based adaptation is possible if vessel shear stress set points are cued to the stress peaks. Model networks that respond to peak stresses alone can quantitatively reproduce the observed zebrafish trunk microcirculation, including its adaptive trajectory when hematocrit changes or parts of the network are amputated. Our work reveals the potential for mechanotransduction alone to generate stable hydraulically tuned microvascular networks.

FMRP stalls ribosomal translocation on mRNAs linked to synaptic function and autism.

FMRP loss of function causes Fragile X syndrome (FXS) and autistic features. FMRP is a polyribosome-associated neuronal RNA-binding protein, suggesting that it plays a key role in regulating neuronal translation, but there has been little consensus regarding either its RNA targets or mechanism of action. Here, we use high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP) to identify FMRP interactions with mouse brain polyribosomal mRNAs. FMRP interacts with the coding region of transcripts encoding pre- and postsynaptic proteins and transcripts implicated in autism spectrum disorders (ASD). We developed a brain polyribosome-programmed translation system, revealing that FMRP reversibly stalls ribosomes specifically on its target mRNAs. Our results suggest that loss of a translational brake on the synthesis of a subset of synaptic proteins contributes to FXS. In addition, they provide insight into the molecular basis of the cognitive and allied defects in FXS and ASD and suggest multiple targets for clinical intervention.

Multiple models for outbreak decision support in the face of uncertainty.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

Cluster analysis dissecting cognitive deficits in older adults with major depressive disorder and the association with neurofilament light chain.

BACKGROUND: Cognitive impairment is a growing problem with increasing burden in global aging. Older adults with major depressive disorder (MDD) have higher risk of dementia. Neurofilament light chain (NfL) has been proven as a potential biomarker in neurodegenerative disease, including dementia. We aimed to investigate the association between cognitive deficits and NfL levels in older adults with MDD. METHODS: In this cross-sectional study, we enrolled 39 MDD patients and 15 individuals with mild neurocognitive disorder or major neurocognitive disorder, Alzheimer's type, as controls, from a tertiary psychiatric hospital. Both groups were over age 65 and with matched Mini-Mental State Examination (MMSE) score. Demographic data, clinical variables, and plasma NfL levels were obtained. We used cluster analysis according to their cognitive profile and estimated the correlation between plasma NfL levels and each cognitive domain. RESULTS: In the MDD group, participants had higher rate of family psychiatry history and current alcohol use habit compared with controls. Control group of neurocognitive disorders showed significantly lower score in total MMSE and higher plasma NfL levels. Part of the MDD patients presented cognitive deficits clustered with that of neurocognitive disorders (cluster A). In cluster A, the total MMSE score (r=-0.58277, p=0.0287) and the comprehension domain (r=-0.71717, p=0.0039) were negatively correlated to NfL levels after adjusting for age, while the associations had not been observed in the other cluster. CONCLUSIONS: We noted the negative correlation between NfL levels and cognition in MDD patients clustered with neurodegenerative disorder, Alzheimer's type. NfL could be a promising candidate as a biomarker to predict subtype of patients in MDD to develop cognitive decline. Further longitudinal studies and within MDD cluster analysis are required to validate our findings for clinical implications.

Physical Activity Trends Among Adults in a National Mobile Health Program: A Population-Based Cohort Study of 411,528 Adults.

Physical inactivity is a global public health challenge, and effective, large-scale interventions are needed. We examined the effectiveness of a population-wide mobile health (mHealth) intervention in Singapore, National Steps Challenge Season 3 (NSC3) and 2 booster challenges (Personal Pledge and Corporate Challenge). The study includes 411,528 participants. We used regression discontinuity design and difference-in-difference with fixed-effects regression to examine the association of NSC3 and the additional booster challenges on daily step counts. Participants tended to be female (58.5%), with an average age of 41.5 years (standard deviation, 13.9) and body mass index (weight (kg)/height (m)2) of 23.8 (standard deviation, 4.5). We observed that NSC3 was associated with a mean increase of 1,437 steps (95% confidence interval (CI): 1,408, 1,467) per day. Enrollments in Personal Pledge and Corporate Challenge were associated with additional mean increases of 1,172 (95% CI: 1,123, 1,222) and 896 (95% CI: 862, 930) steps per day, respectively. For NSC3, the associated mean increase in the step counts across different sex and age groups varied, with greater increases for female participants and those in the oldest age group. We provide real-world evidence suggesting that NSC3 was associated with improvements in participants' step counts. Results suggest NSC3 is an effective and appealing population-wide mHealth physical activity intervention.

Indole-3-Propionic Acid, a Gut Microbiota Metabolite, Protects Against the Development of Postoperative Delirium.

OBJECTIVE: The aim was to determine preoperative gut microbiota metabolites that may be associated with postoperative delirium (POD) development in patients and further study in rodents. SUMMARY BACKGROUND DATA: POD occurs in 9% to 50% of older patients undergoing anesthesia/surgery but lacks effective treatments or prevention. High-throughput metabolomics using liquid chromatography with tandem mass spectrometry has accelerated disease-related biomarkers discovery. We performed metabolomic studies in humans to identify potential metabolite biomarkers linked to POD and examined potential mechanisms in rodents. METHODS: We performed a prospective observational cohort study to examine the metabolomic changes that were associated with the development of POD. Then the gut microbiota-related metabolomic changes were recapitulated by gut microbiota perturbation in rodents. POD was assessed in mice using a battery of behavioral tests including novel objective test, Y-maze test, open-field test, and buried food test. The mechanisms through which gut microbiota-related metabolomic changes influenced POD were examined using chemogenetics. RESULTS: Indole-3-propionic acid (IPA) is a gut microbiota metabolite that belongs to the indole family. Baseline plasma levels of IPA were significantly inversely correlated with the onset of POD in 103 (17 cases) human individuals. This relationship was validated in preclinical mouse models for POD: reducing IPA levels through gut microbiota perturbation promoted POD-like behavior. More importantly, IPA administration deterred POD-like behavior. Colonization of germ-free mice with mutant Clostridium sporogenes that did not produce IPA-promoted POD-like behavior. Chemogenetic studies revealed that the protective effect of IPA in mice was mediated, in part, by peroxisome proliferator-activated receptor gamma coactivator 1-alpha in hippocampal interneurons. CONCLUSIONS: Gut microbiota-derived IPA is an important molecule implicated in the pathogenesis of POD, which could potentially be harnessed for POD prevention.

Societal Adaptation to Aging and Prevalence of Depression Among Older Adults: Evidence From 20 Countries.

Policy Points Countries have adopted different strategies to support aging populations, which are broadly reflected in social, economic, and contextual environments. Referred to as "societal adaptation to aging," these factors affect countries' capacity to support older adults. Results from our study show that countries with more robust societal adaptation to aging had lower depression prevalence. Reductions in depression prevalence occurred among every investigated sociodemographic group and were most pronounced among the old-old. Findings suggest that societal factors have an underacknowledged role in shaping depression risk. Policies that improve societal approaches to aging may reduce depression prevalence among older adults. CONTEXT: Countries have adopted various formal and informal approaches to support older adults, which are broadly reflected in different policies, programs, and social environments. These contextual environments, broadly referred to as "societal adaptation to aging," may affect population health. METHODS: We used a new theory-based measure that captured societal adaptation to aging, the Aging Society Index (ASI), which we linked with harmonized individual-level data from 89,111 older adults from 20 countries. Using multi-levels models that accounted for differences in the population composition across countries, we estimated the association between country-level ASI scores and depression prevalence. We also tested if associations were stronger among the old-old and among sociodemographic groups that experience more disadvantage (i.e., women, those with lower educational attainment, unmarried adults). FINDINGS: We found that countries with higher ASI scores, indicating more comprehensive approaches to supporting older adults, had lower depression prevalence. We found especially strong reductions in depression prevalence among the oldest adults in our sample. However, we did not find stronger reductions among sociodemographic groups who may experience more disadvantage. CONCLUSIONS: Country-level strategies to support older adults may affect depression prevalence. Such strategies may become increasingly important as adults grow older. These results offer promising evidence that improvements in societal adaptation to aging-such as through adoption of more comprehensive policies and programs targeting older adults-may be one avenue to improve population mental health. Future research could investigate observed associations using longitudinal and quasi-experimental study designs, offering additional information regarding a potential causal relationship.

Lymphatic endothelial S1P promotes mitochondrial function and survival in naive T cells.

Effective adaptive immune responses require a large repertoire of naive T cells that migrate throughout the body, rapidly identifying almost any foreign peptide. Because the production of T cells declines with age, naive T cells must be long-lived. However, it remains unclear how naive T cells survive for years while constantly travelling. The chemoattractant sphingosine 1-phosphate (S1P) guides T cell circulation among secondary lymphoid organs, including spleen, lymph nodes and Peyer's patches, where T cells search for antigens. The concentration of S1P is higher in circulatory fluids than in lymphoid organs, and the S1P1 receptor (S1P1R) directs the exit of T cells from the spleen into blood, and from lymph nodes and Peyer's patches into lymph. Here we show that S1P is essential not only for the circulation of naive T cells, but also for their survival. Using transgenic mouse models, we demonstrate that lymphatic endothelial cells support the survival of T cells by secreting S1P via the transporter SPNS2, that this S1P signals through S1P1R on T cells, and that the requirement for S1P1R is independent of the established role of the receptor in guiding exit from lymph nodes. S1P signalling maintains the mitochondrial content of naive T cells, providing cells with the energy to continue their constant migration. The S1P signalling pathway is being targeted therapeutically to inhibit autoreactive T cell trafficking, and these findings suggest that it may be possible simultaneously to target autoreactive or malignant cell survival.

The societal cost of modifiable risk factors in Singapore.

BACKGROUND: Singapore is one of the most rapidly ageing populations in the world. Nearly half of all disease burdens in Singapore are attributable to modifiable risk factors. This indicates that many illnesses are preventable by modifying behaviours such as increasing physical activity levels or maintaining a healthy diet. Prior cost-of-illness studies have estimated the cost of selected modifiable risk factors. However, no local study has compared costs between groups of modifiable risks. This study aims to estimate the societal cost attributable to a comprehensive list of modifiable risks in Singapore. METHODS: Our study builds on the comparative risk assessment framework from the Global Burden of Disease (GBD) 2019 study. A top-down prevalence-based cost-of-illness approach was undertaken to estimate the societal cost of modifiable risks in 2019. These include healthcare costs from inpatient hospitalisation and productivity losses from absenteeism and premature mortality. RESULTS: Metabolic risks had the highest total cost of US$1.62 billion (95% uncertainty interval [UI] US$1.51-1.84 billion), followed by lifestyle risks of US$1.40 billion (95% UI US$1.36-1.66 billion) and substance risks of US$1.15 billion (95% UI US$1.10-1.24 billion). Across the risk factors, the costs were driven by productivity losses, heavily skewed towards the older working-age group and among males. Most of the costs were driven by cardiovascular diseases. CONCLUSION: This study provides evidence of the high societal cost of modifiable risks and highlights the importance of developing holistic public health promotion programmes. As modifiable risks often do not occur in isolation, implementing effective population-based programmes targeting multiple modifiable risks has a strong potential to manage the cost of the rising disease burden in Singapore.

Identifying the sociodemographic and work-related factors related to workers' daily physical activity using a decision tree approach.

BACKGROUND: The social and behavioural factors related to physical activity among adults are well known. Despite the overlapping nature of these factors, few studies have examined how multiple predictors of physical activity interact. This study aimed to identify the relative importance of multiple interacting sociodemographic and work-related factors associated with the daily physical activity patterns of a population-based sample of workers. METHODS: Sociodemographic, work, screen time, and health variables were obtained from five, repeated cross-sectional cohorts of workers from the Canadian Health Measures Survey (2007 to 2017). Classification and Regression Tree (CART) modelling was used to identify the discriminators associated with six daily physical activity patterns. The performance of the CART approach was compared to a stepwise multinomial logistic regression model. RESULTS: Among the 8,909 workers analysed, the most important CART discriminators of daily physical activity patterns were age, job skill, and physical strength requirements of the job. Other important factors included participants' sex, educational attainment, fruit/vegetable intake, industry, work hours, marital status, having a child living at home, computer time, and household income. The CART tree had moderate classification accuracy and performed marginally better than the stepwise multinomial logistic regression model. CONCLUSION: Age and work-related factors-particularly job skill, and physical strength requirements at work-appeared as the most important factors related to physical activity attainment, and differed based on sex, work hours, and industry. Delineating the hierarchy of factors associated with daily physical activity may assist in targeting preventive strategies aimed at promoting physical activity in workers.

Impact of the value driven outcomes program among cataract surgery patients in Singapore: an interrupted time series analysis.

BACKGROUND: Healthcare cost is increasing rapidly in Singapore. Moving towards a value-based healthcare framework enables a sustainable health system. The National University Hospital (NUH) implemented the Value Driven Outcome (VDO) Program for cataract surgery due to its high volume and cost variability. We aimed to evaluate the association between VDO program implementation and costs and quality outcomes for cataract surgery in NUH. METHODS: We conducted an interrupted time-series analysis for cataract surgery episodes between January 2015 and December 2018. Using segmented linear regression models, we estimate the changes in levels and trends of cost and quality outcomes post-program implementation. We adjusted for autoregression and various confounders. RESULTS: Following VDO program implementation, the total cost of cataract surgery had a significantly decreased by $327.23 (95% CI: -$421.04 to -$233.43; p < 0.01) and the trend significantly decreased by $13.75 per month (95% CI: -$23.19 to -$4.30 per month; p < 0.01). There was a small improvement in the combined quality outcome score (0.028, 95% CI: 0.016 to 0.040; p < 0.01), but the trend remained unchanged. CONCLUSION: The VDO program was associated with a reduction in cost without compromising on quality outcomes. The program provides a structured methodology to measure performances, and through these data, initiatives were implemented to improve value. There are benefits to providing a data reporting system to physicians to understand actual care costs and quality outcomes achieved by individual patients with defined clinical conditions.

Daily accelerometer-measured physical activity patterns and associations with cardiometabolic health among Canadian working adults.

Background: Previous studies examining the cardiometabolic risks associated with physical activity (PA) in workers have predominantly used self-reported measures. Little is known about workers' distinct daily PA patterns and whether these are linked with cardiometabolic risks. This study examined associations between patterns of workers' accelerometer-measured daily PA and four markers of cardiometabolic health. Data and methods: Working adults (N=8,229; 47% women; average age: 42 years; standard deviation = 0.3) were sampled from the Canadian Health Measures Survey (five cycles: 2007 to 2017). Accelerometer devices measured daily PA, and hierarchical cluster analysis identified distinct activity patterns. Multiple linear regression analyses examined associations between activity patterns and cardiometabolic risk markers (waist circumference, systolic and diastolic blood pressure, and non-high-density lipoprotein [HDL] cholesterol). Results: Workers were classified into six distinct activity patterns. On average, compared with workers classified in the "lowest activity" pattern, workers with the "moderate consistent activity," "fluctuating moderate activity," "high daytime activity" and "highest activity" patterns were associated with lower waist circumferences; workers with the "fluctuating moderate activity" and "highest activity" patterns were associated with lower systolic blood pressure; the "moderate evening activity" pattern was associated with lower diastolic blood pressure; and workers with the "fluctuating moderate activity," "high daytime activity" and "highest activity" patterns were associated with lower non-HDL cholesterol. "High daytime activity" was associated with lower waist circumference in women, compared with men, and the "moderate consistent activity" and "fluctuating moderate activity" patterns were associated with lower diastolic blood pressure in younger workers (40 years or younger). Interpretation: Workers with high daily PA levels tended to have the most optimal cardiometabolic health. Some evidence suggested that there are benefits to moderate levels of PA, particularly for lowering waist circumference and non-HDL cholesterol. Findings may assist in identifying workers for PA initiatives to promote cardiometabolic health benefits.

The social cost of high sodium diet in Singapore.

High sodium (Na) diet is one of the leading behavioural risks of disease identified in the Singapore Burden of Disease Study. We aim to estimate the cost attributable to a high Na diet in Singapore in 2019 from a societal perspective by employing a prevalence-based approach in cost-of-illness studies. We extracted national-level healthcare data and population attributable fractions by sex and age. Costs included direct and indirect costs from inpatient treatment and productivity losses. In 2019, the annual societal cost attributable to a high Na diet was conservatively estimated to be USA$262 million (95 % uncertainty interval (UI) 218, 359 million). At least USA$67·8 million (95 % UI 48·4, 120 million) and USA$194 million (95 % UI 153, 274 million) could be saved on healthcare and indirect costs, respectively, if the daily Na intake of Singaporeans was reduced to an average of 3 g. Overall, males had higher costs compared with females at USA$221 million (95 % UI 174, 312 million) and USA$41·1 million (95 % UI 33·5, 61·7 million), respectively. Productivity loss from foregone wages due to premature mortality had the largest cost at USA$191 million (95 % UI 150, 271 million). CVD had the largest healthcare expenditure at USA$61·4 million (95 % UI 41·6, 113 million), driven by ischaemic heart disease at USA$41·0 million (95 % UI 21·4, 88·9 million). Our study found that reducing Na intake could reduce future healthcare expenditures and productivity losses. This result is vital for policy evaluation in a rapidly ageing society like Singapore, where the burden of diseases associated with high Na diet is expected to increase.

Benchmarking ensemble docking methods in D3R Grand Challenge 4.

The discovery of new drugs is a time consuming and expensive process. Methods such as virtual screening, which can filter out ineffective compounds from drug libraries prior to expensive experimental study, have become popular research topics. As the computational drug discovery community has grown, in order to benchmark the various advances in methodology, organizations such as the Drug Design Data Resource have begun hosting blinded grand challenges seeking to identify the best methods for ligand pose-prediction, ligand affinity ranking, and free energy calculations. Such open challenges offer a unique opportunity for researchers to partner with junior students (e.g., high school and undergraduate) to validate basic yet fundamental hypotheses considered to be uninteresting to domain experts. Here, we, a group of high school-aged students and their mentors, present the results of our participation in Grand Challenge 4 where we predicted ligand affinity rankings for the Cathepsin S protease, an important protein target for autoimmune diseases. To investigate the effect of incorporating receptor dynamics on ligand affinity rankings, we employed the Relaxed Complex Scheme, a molecular docking method paired with molecular dynamics-generated receptor conformations. We found that Cathepsin S is a difficult target for molecular docking and we explore some advanced methods such as distance-restrained docking to try to improve the correlation with experiments. This project has exemplified the capabilities of high school students when supported with a rigorous curriculum, and demonstrates the value of community-driven competitions for beginners in computational drug discovery.

Crosstalk between Schizophrenia and Metabolic Syndrome: The Role of Oxytocinergic Dysfunction.

The high prevalence of metabolic syndrome in persons with schizophrenia has spurred investigational efforts to study the mechanism beneath its pathophysiology. Early psychosis dysfunction is present across multiple organ systems. On this account, schizophrenia may be a multisystem disorder in which one organ system is predominantly affected and where other organ systems are also concurrently involved. Growing evidence of the overlapping neurobiological profiles of metabolic risk factors and psychiatric symptoms, such as an association with cognitive dysfunction, altered autonomic nervous system regulation, desynchrony in the resting-state default mode network, and shared genetic liability, suggest that metabolic syndrome and schizophrenia are connected via common pathways that are central to schizophrenia pathogenesis, which may be underpinned by oxytocin system dysfunction. Oxytocin, a hormone that involves in the mechanisms of food intake and metabolic homeostasis, may partly explain this piece of the puzzle in the mechanism underlying this association. Given its prosocial and anorexigenic properties, oxytocin has been administered intranasally to investigate its therapeutic potential in schizophrenia and obesity. Although the pathophysiology and mechanisms of oxytocinergic dysfunction in metabolic syndrome and schizophrenia are both complex and it is still too early to draw a conclusion upon, oxytocinergic dysfunction may yield a new mechanistic insight into schizophrenia pathogenesis and treatment.

A Learning Framework for Personalized Random Utility Maximization (RUM) Modeling of User Behavior.

Understanding user behavior is crucial for the success of many emerging applications that aim to provide personalized services for target users, such as many patient-centered health apps and transportation apps. Models based on the random utility maximization (RUM) theory are widely used in learning and understanding behavioral preferences on the population level but find difficult to estimate individuals' preferences, particularly when individuals' data are limited and fragmented. To address this problem, our framework builds on the concepts such as canonical structure and membership vectors invented in recent works on collaborative learning and is suitable for modeling heterogeneous population with insufficient data from each individual. We further propose an extension of the collaborative learning framework using pairwise-fusion regularization as a knowledge discovery tool for real-world applications where the canonical structure is uneven, e.g., some canonical models may only represent minor subpopulations. Computationally competent algorithms are developed to solve the corresponding optimization challenges. Extensive simulation studies and a real-world application in smart transportation demand management (TDM) show the effectiveness of our proposed methods.

A Call for Caution in Use of Pertussis Vaccine Effectiveness Studies to Estimate Waning Immunity: A Canadian Immunization Research Network Study.

BACKGROUND: Vaccine effectiveness (VE) studies provide essential evidence on waning vaccine-derived immunity, a major threat to pertussis control. We evaluated how study design affects estimates by comparing 2 case-control studies conducted in Ontario, Canada. METHODS: We compared results from a test-negative design (TND) with a frequency-matched design (FMD) case-control study using pertussis cases from 2005-2015. In the first study, we identified test-negative controls from the public health laboratory that diagnosed cases and, in the second, randomly selected controls from patients attending the same physicians that reported cases, frequency matched on age and year. We compared characteristics of cases and controls using standardized differences. RESULTS: In both designs, VE estimates for the early years postimmunization were consistent with clinical trials (TND, 84%; FMD, 89% at 1-3 years postvaccination) but diverged as time since last vaccination increased (TND, 41%; FMD, 74% by 8 years postvaccination). Overall, we observed lower VE and faster waning in the TND than the FMD. In the TND but not FMD, controls differed from cases in important confounders, being younger, having more comorbidities, and higher healthcare use. Differences between the controls of each design were greater than differences between cases. TND controls were more likely to be unvaccinated or incompletely vaccinated than FMD controls (P < .001). CONCLUSIONS: The FMD adjusted better for healthcare-seeking behavior than the TND. Duration of protection from pertussis vaccines is unclear because estimates vary by study design. Caution should be exercised by experts, researchers, and decision makers when evaluating evidence on optimal timing of boosters.

Changes in Diet Quality from Mid- to Late Life Are Associated with Cognitive Impairment in the Singapore Chinese Health Study.

BACKGROUND: Although higher diet quality at mid-life has been associated with better cognitive function in late adulthood, it is unclear whether dietary improvement after mid-life may reduce the risk of cognitive impairment. OBJECTIVES: We examined associations between changes in diet quality and risk of cognitive impairment in the Singapore Chinese Health Study cohort. METHODS: We used data from 14,683 Chinese men and women who were recruited at ages 45 to 74 y from 1993 to 1998 and re-interviewed after 20 y at ages 61 to 96 y during follow-up 3 (2014-2016). Diet quality was measured using the Dietary Approaches to Stop Hypertension (DASH) scores at baseline and follow-up 3 interviews. Cognitive impairment was defined using scores from the Singapore-modified Mini-Mental State Examination at the follow-up 3 interview. Multivariable logistic regression models were used to estimate ORs and 95% CIs for the associations between change in DASH scores and cognitive impairment. RESULTS: Higher quintiles in DASH scores at baseline and follow-up 3 interviews were associated with lower odds of cognitive impairment in a dose-dependent manner (both: P-trend < 0.001). Compared with participants with consistently low DASH scores, the OR (95% CI) of cognitive impairment was lowest, at 0.64 (0.51, 0.79), in those with consistently high DASH scores. Those with small (OR: 0.80, 95% CI: 0.65, 0.98) or moderate-large (OR: 0.72, 95% CI: 0.59, 0.86) increases in DASH scores were associated with significantly lower odds of cognitive impairment than those with consistently low DASH scores. Associations were consistent across subgroups by sex, BMI (kg/m2; <23 or ≥23), and age (<60 y, ≥60 y) at baseline. CONCLUSIONS: Although maintaining high diet quality confers the lowest risk, improving diet quality from mid- to late life was still associated with a lower risk of cognitive impairment in late adulthood.