Adjustment for selection bias in observational studies with application to the analysis of autopsy data

Estimating the Effect of PrEP in Black Men Who Have Sex with Men: A Framework to Utilize Data from Multiple Non-Randomized Studies to Estimate Causal Effects

Black men who have sex with men (MSM) are disproportionately burdened by the HIV epidemic in the US. The effectiveness of pre-exposure prophylaxis (PrEP) in preventing HIV infection has been demonstrated through randomized placebo-controlled clinical trials in several populations. Importantly, no such trial has been conducted exclusively among Black MSM in the US, and it would be unethical and infeasible to do so now. To estimate the causal effects of PrEP access, initiation, and adherence on HIV risk, we utilized causal inference methods to combine data from two non-randomized studies that exclusively enrolled Black MSM. The estimated relative risks of HIV were: (i) 0.52 (95% confidence interval: 0.21, 1.22) for individuals with versus without PrEP access, (ii) 0.48 (0.12, 0.89) for individuals who initiated PrEP but were not adherent versus those who did not initiate, and (iii) 0.23 (0.02, 0.80) for individuals who were adherent to PrEP versus those who did not initiate. Beyond addressing the knowledge gap around the effect of PrEP in Black MSM in the US, which may have ramifications for public health, we have provided a framework to combine data from multiple non-randomized studies to estimate causal effects, which has broad utility.

Different cohort, disparate results: Selection bias is a key factor in autopsy cohorts

INTRODUCTION

Research-oriented autopsy cohorts provide critical insights into dementia pathobiology. However, different studies sometimes report disparate findings, partially because each study has its own recruitment biases. We hypothesized that a straightforward metric, related to the percentage of research volunteers cognitively normal at recruitment, would predict other inter-cohort differences.

METHODS

The National Alzheimer's Coordinating Center (NACC) provided data on N = 7178 autopsied participants from 28 individual research centers. Research cohorts were grouped based on the proportion of participants with normal cognition at initial clinical visit.

RESULTS

Cohorts with more participants who were cognitively normal at recruitment contained more individuals who were older, female, had lower frequencies of apolipoprotein E ε4, Lewy body disease, and frontotemporal dementia, but higher rates of cerebrovascular disease. Alzheimer's disease (AD) pathology was little different between groups.

DISCUSSION

The percentage of participants recruited while cognitively normal predicted differences in findings in autopsy research cohorts. Most differences were in non-AD pathologies.

HIGHLIGHTS

Systematic differences exist between autopsy cohorts that serve dementia research. We propose a metric to use for gauging a research-oriented autopsy cohort. It is essential to consider the characteristics of autopsy cohorts.

Year-by-Year Blood Pressure Variability From Midlife to Death and Lifetime Dementia Risk

Importance

High visit-to-visit blood pressure variability (BPV) in late life may reflect increased dementia risk better than mean systolic blood pressure (SBP). Evidence from midlife to late life could be crucial to understanding this association.

Objective

To determine whether visit-to-visit BPV at different ages was differentially associated with lifetime incident dementia risk in community-dwelling individuals.

Design, Setting, and Participants

This cohort study analyzed data from the Adult Changes in Thought (ACT) study, an ongoing population-based prospective cohort study in the US. Participants were 65 years or older at enrollment, community-dwelling, and without dementia. The study focused on a subset of deceased participants with brain autopsy data and whose midlife to late-life blood pressure data were obtained from Kaiser Permanente Washington medical archives and collected as part of the postmortem brain donation program. In the ACT study, participants underwent biennial medical assessments, including cognitive screening. Data were collected from 1994 (ACT study enrollment) through November 2019 (data set freeze). Data analysis was performed between March 2020 and September 2023.

Exposures

Visit-by-visit BPV at ages 60, 70, 80, and 90 years, calculated using the coefficient of variation of year-by-year SBP measurements over the preceding 10 years.

Main Outcomes and Measures

All-cause dementia, which was adjudicated by a multidisciplinary outcome adjudication committee.

Results

A total of 820 participants (mean [SD] age at enrollment, 77.0 [6.7] years) were analyzed and included 476 females (58.0%). A mean (SD) of 28.4 (8.4) yearly SBP measurements were available over 31.5 (9.0) years. The mean (SD) follow-up time was 32.2 (9.1) years in 27 885 person-years from midlife to death. Of the participants, 372 (45.4%) developed dementia. The number of participants who were alive without dementia and had available data for analysis ranged from 280 of those aged 90 years to 702 of those aged 70 years. Higher BPV was not associated with higher lifetime dementia risk at age 60, 70, or 80 years. At age 90 years, BPV was associated with 35% higher dementia risk (hazard ratio [HR], 1.35; 95% CI, 1.02-1.79). Meta-regression of HRs calculated separately for each age (60-90 years) indicated that associations of high BPV with higher dementia risk were present only at older ages, whereas the association of SBP with dementia gradually shifted direction linearly from being incrementally to inversely associated with older ages.

Conclusions and Relevance

In this cohort study, high BPV indicated increased lifetime dementia risk in late life but not in midlife. This result suggests that high BPV may indicate increased dementia risk in older age but might be less viable as a midlife dementia prevention target.

A neuropathologic feature of brain aging: multi-lumen vascular profiles

Cerebrovascular pathologies other than frank infarctions are commonly seen in aged brains. Here, we focus on multi-lumen vascular profiles (MVPs), which are characterized by multiple vessel lumens enclosed in a single vascular channel. Little information exists on the prevalence, risk factors, and co-pathologies of MVPs. Therefore, we used samples and data from the University of Kentucky Alzheimer's Disease Research Center (n = 91), the University of Kentucky Pathology Department (n = 31), and the University of Pittsburgh Pathology Department (n = 4) to study MVPs. Age at death was correlated with MVP density in the frontal neocortex, Brodmann Area 9 (r = 0.51; p < 0.0001). Exploratory analyses were performed to evaluate the association between conventional vascular risk factors (e.g., hypertension, diabetes), cardiovascular diseases (e.g., heart attack, arrhythmia), and cerebrovascular disease (e.g., stroke); the only nominal association with MVP density was a self-reported history of brain trauma (Prevalence Ratio = 2.1; 95 CI 1.1-3.9, before correcting for multiple comparisons). No specific associations were detected between neuropathological (e.g., brain arteriolosclerosis) or genetic (e.g., APOE) variables and MVP density. Using a tissue clearing method called SeeDB, we provide 3-dimensional images of MVPs in brain tissue. We conclude that MVPs are an age-related brain pathology and more work is required to identify their clinical-pathological correlation and associated risk factors.

Avoiding Biased Clinical Machine Learning Model Performance Estimates in the Presence of Label Selection

When evaluating the performance of clinical machine learning models, one must consider the deployment population. When the population of patients with observed labels is only a subset of the deployment population (label selection), standard model performance estimates on the observed population may be misleading. In this study we describe three classes of label selection and simulate five causally distinct scenarios to assess how particular selection mechanisms bias a suite of commonly reported binary machine learning model performance metrics. Simulations reveal that when selection is affected by observed features, naive estimates of model discrimination may be misleading. When selection is affected by labels, naive estimates of calibration fail to reflect reality. We borrow traditional weighting estimators from causal inference literature and find that when selection probabilities are properly specified, they recover full population estimates. We then tackle the real-world task of monitoring the performance of deployed machine learning models whose interactions with clinicians feed-back and affect the selection mechanism of the labels. We train three machine learning models to flag low-yield laboratory diagnostics, and simulate their intended consequence of reducing wasteful laboratory utilization. We find that naive estimates of AUROC on the observed population undershoot actual performance by up to 20%. Such a disparity could be large enough to lead to the wrongful termination of a successful clinical decision support tool. We propose an altered deployment procedure, one that combines injected randomization with traditional weighted estimates, and find it recovers true model performance.

Direct Effect of Life-Course Socioeconomic Status on Late-Life Cognition and Cognitive Decline in the Rush Memory and Aging Project

The role of socioeconomic status (SES) across the life course in late-life cognition is unclear. We tested the hypotheses that: 1) High SES in childhood, young adulthood, midlife, and late life have independent causal effects on higher cognition level and slower cognitive decline; 2) Compared with stable low SES (referent), stable high SES has the largest estimated effect for higher cognition level and slower decline among life-course SES combinations. The Rush Memory and Aging Project enrolled 1,940 dementia-free older adults in northeastern Illinois (1997-2018). We used inverse probability-weighted marginal structural models to estimate the joint and independent effect of each life-course SES on global and domain-specific cognition. A total of 1,746 participants had, on average, 6 years of follow-up. High SES at each life-course stage starting in young adulthood had a protective estimated effect on global and domain-specific cognition intercepts. Compared with consistently low SES, consistently high SES (β = 0.64, 95% confidence interval: 0.48, 0.93) and high SES beyond childhood (β = 0.64, 95% confidence interval: 0.47, 0.83) had the largest benefit for global cognition intercepts. None of the life-course SES measures influenced rate of global or domain-specific decline. Additional understanding of life-course SES components influencing cognitive level is warranted.

Air pollution and dementia in older adults in the Ginkgo Evaluation of Memory Study

INTRODUCTION

Growing evidence implicates air pollution as a risk factor for dementia, but prior work is limited by challenges in diagnostic accuracy and assessing exposures in the decades prior to disease development. We evaluated the impact of long-term fine particulate matter (PM2.5 ) exposures on incident dementia (all-cause, Alzheimer's disease [AD], and vascular dementia [VaD]) in older adults.

METHODS

A panel of neurologists adjudicated dementia cases based on extensive neuropsychological testing and magnetic resonance imaging. We applied validated fine-scale air pollutant models to reconstructed residential histories to assess exposures.

RESULTS

An interquartile range increase in 20-year PM2.5 was associated with a 20% higher risk of dementia (95% confidence interval [CI]: 5%, 37%) and an increased risk of mixed VaD/AD but not AD alone.

DISCUSSION

Our findings suggest that air pollutant exposures over decades contribute to dementia and that effects of current exposures may be experienced years into the future.

Association of Traumatic Brain Injury with Late Life Neuropathological Outcomes in a Community-Based Cohort

BACKGROUND

Prior studies into the association of head trauma with neuropathology have been limited by incomplete lifetime neurotrauma exposure characterization.

OBJECTIVE

To investigate the neuropathological sequelae of traumatic brain injury (TBI) in an autopsy sample using three sources of TBI ascertainment, weighting findings to reflect associations in the larger, community-based cohort.

METHODS

Self-reported head trauma with loss of consciousness (LOC) exposure was collected in biennial clinic visits from 780 older adults from the Adult Changes in Thought study who later died and donated their brain for research. Self-report data were supplemented with medical record abstraction, and, for 244 people, structured interviews on lifetime head trauma. Neuropathology outcomes included Braak stage, CERAD neuritic plaque density, Lewy body distribution, vascular pathology, hippocampal sclerosis, and cerebral/cortical atrophy. Exposures were TBI with or without LOC. Modified Poisson regressions adjusting for age, sex, education, and APOE ɛ4 genotype were weighted back to the full cohort of 5,546 participants.

RESULTS

TBI with LOC was associated with the presence of cerebral cortical atrophy (Relative Risk 1.22, 95% CI 1.02, 1.42). None of the other outcomes was associated with TBI with or without LOC.

CONCLUSION

TBI with LOC was associated with increased risk of cerebral cortical atrophy. Despite our enhanced TBI ascertainment, we found no association with the Alzheimer's disease-related neuropathologic outcomes among people who survived to at least age 65 without dementia. This suggests the pathophysiological processes underlying post-traumatic neurodegeneration are distinct from the hallmark pathologies of Alzheimer's disease.

Leveraging electronic health records for data science: common pitfalls and how to avoid them

Analysis of electronic health records (EHRs) is an increasingly common approach for studying real-world patient data. Use of routinely collected data offers several advantages compared with other study designs, including reduced administrative costs, the ability to update analysis as practice patterns evolve, and larger sample sizes. Methodologically, EHR analysis is subject to distinct challenges because data are not collected for research purposes. In this Viewpoint, we elaborate on the importance of in-depth knowledge of clinical workflows and describe six potential pitfalls to be avoided when working with EHR data, drawing on examples from the literature and our experience. We propose solutions for prevention or mitigation of factors associated with each of these six pitfalls-sample selection bias, imprecise variable definitions, limitations to deployment, variable measurement frequency, subjective treatment allocation, and model overfitting. Ultimately, we hope that this Viewpoint will guide researchers to further improve the methodological robustness of EHR analysis.

Multiple gene variants linked to Alzheimer's-type clinical dementia via GWAS are also associated with non-Alzheimer's neuropathologic entities

The classic pathologic hallmarks of Alzheimer's disease (AD) are amyloid plaques and neurofibrillary tangles (AD neuropathologic changes, or ADNC). However, brains from individuals clinically diagnosed with "AD-type" (amnestic) dementia usually harbor heterogeneous neuropathologies in addition to, or other than, ADNC. We hypothesized that some AD-type dementia associated genetic single nucleotide variants (SNVs) identified from large genomewide association studies (GWAS) were associated with non-ADNC neuropathologies. To test this hypothesis, we analyzed data from multiple studies with available genotype and neuropathologic phenotype information. Clinical AD/dementia risk alleles of interest were derived from the very large GWAS by Bellenguez et al. (2022) who reported 83 clinical AD/dementia-linked SNVs in addition to the APOE risk alleles. To query the pathologic phenotypes associated with variation of those SNVs, National Alzheimer's disease Coordinating Center (NACC) neuropathologic data were linked to AD Sequencing Project (ADSP) and AD Genomics Consortium (ADGC) data. Separate data were obtained from the harmonized Religious Orders Study and the Rush Memory and Aging Project (ROSMAP). A total of 4811 European participants had at least ADNC neuropathology data and also genotype data available; data were meta-analyzed across cohorts. As expected, a subset of dementia-associated SNVs were associated with ADNC risk in Europeans-e.g., BIN1, PICALM, CR1, MME, and COX7C. Other gene variants linked to (clinical) AD dementia were associated with non-ADNC pathologies. For example, the associations of GRN and TMEM106B SNVs with limbic-predominant age-related TDP-43 neuropathologic changes (LATE-NC) were replicated. In addition, SNVs in TNIP1 and WNT3 previously reported as AD-related were instead associated with hippocampal sclerosis pathology. Some genotype/neuropathology association trends were not statistically significant at P < 0.05 after correcting for multiple testing, but were intriguing. For example, variants in SORL1 and TPCN1 showed trends for association with LATE-NC whereas Lewy body pathology trended toward association with USP6NL and BIN1 gene variants. A smaller cohort of non-European subjects (n = 273, approximately one-half of whom were African-Americans) provided the basis for additional exploratory analyses. Overall, these findings were consistent with the hypothesis that some genetic variants linked to AD dementia risk exert their affect by influencing non-ADNC neuropathologies.

Interpretable deep learning of myelin histopathology in age-related cognitive impairment

Age-related cognitive impairment is multifactorial, with numerous underlying and frequently co-morbid pathological correlates. Amyloid beta (Aβ) plays a major role in Alzheimer's type age-related cognitive impairment, in addition to other etiopathologies such as Aβ-independent hyperphosphorylated tau, cerebrovascular disease, and myelin damage, which also warrant further investigation. Classical methods, even in the setting of the gold standard of postmortem brain assessment, involve semi-quantitative ordinal staging systems that often correlate poorly with clinical outcomes, due to imperfect cognitive measurements and preconceived notions regarding the neuropathologic features that should be chosen for study. Improved approaches are needed to identify histopathological changes correlated with cognition in an unbiased way. We used a weakly supervised multiple instance learning algorithm on whole slide images of human brain autopsy tissue sections from a group of elderly donors to predict the presence or absence of cognitive impairment (n = 367 with cognitive impairment, n = 349 without). Attention analysis allowed us to pinpoint the underlying subregional architecture and cellular features that the models used for the prediction in both brain regions studied, the medial temporal lobe and frontal cortex. Despite noisy labels of cognition, our trained models were able to predict the presence of cognitive impairment with a modest accuracy that was significantly greater than chance. Attention-based interpretation studies of the features most associated with cognitive impairment in the top performing models suggest that they identified myelin pallor in the white matter. Our results demonstrate a scalable platform with interpretable deep learning to identify unexpected aspects of pathology in cognitive impairment that can be translated to the study of other neurobiological disorders.

Cancer diagnosis is associated with a lower burden of dementia and less Alzheimer's-type neuropathology

Cancer and Alzheimer's disease are common diseases in ageing populations. Previous research has reported a lower incidence of Alzheimer's disease-type (amnestic) dementia among individuals with a diagnosis of cancer. Both cancer and amnestic dementia are prevalent and potentially lethal clinical syndromes. The current study was conducted to investigate the association of cancer diagnosis with neuropathological and cognitive features of dementia. Data were analysed from longitudinally evaluated participants in a community-based cohort study of brain ageing who came to autopsy at the University of Kentucky Alzheimer's Disease Research Center. These data were linked to the Kentucky Cancer Registry, a population-based state cancer surveillance system, to obtain cancer-related data. We examined the relationship between cancer diagnosis, clinical dementia diagnosis, Mini-Mental State Examination scores and neuropathological features using inverse probability weighting to address bias due to confounding and missing data. To address bias due to inclusion of participants with dementia at cohort baseline, we repeated all analyses restricted to the participants who were cognitively normal at baseline. Included participants (n = 785) had a mean ± standard deviation age of death of 83.8 ± 8.6 years; 60.1% were female. Cancer diagnosis was determined in 190 (24.2%) participants, and a diagnosis of mild cognitive impairment or dementia was determined in 539 (68.7%). APOE ɛ4 allele dosage was lower among participants with cancer diagnosis compared to cancer-free participants overall (P = 0.0072); however, this association was not observed among those who were cognitively normal at baseline. Participants with cancer diagnosis had lower odds of mild cognitive impairment or dementia, and higher cognitive test scores (e.g. Mini-Mental State Examination scores evaluated 6 and ≤2 years ante-mortem, P < 0.001 for both comparisons). Cancer diagnosis also associated with lower odds of higher Braak neurofibrillary tangle stages (III/IV) or (V/VI), moderate/frequent neuritic plaques, moderate/frequent diffuse plaques and moderate/severe cerebral amyloid angiopathy (all P < 0.05). By contrast, TDP-43, α-synuclein and cerebrovascular pathologies were not associated with cancer diagnosis. Cancer diagnosis was associated with a lower burden of Alzheimer's disease pathology and less cognitive impairment. These findings from a community-based cohort with neuropathological confirmation of substrates support the hypothesis that there is an inverse relationship between cancer and Alzheimer's disease.

Relationship Between Level of American Football Playing and Diagnosis of Chronic Traumatic Encephalopathy in a Selection Bias Analysis

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts such as those from American football. Our understanding of this association is based on research in autopsied brains, since CTE can only be diagnosed postmortem. Such studies are susceptible to selection bias, which needs to be accounted for to ensure a generalizable estimate of the association between repetitive head impacts and CTE. We evaluated the relationship between level of American football playing and CTE diagnosis after adjusting for selection bias. The sample included 290 deceased male former American football players who donated their brains to the Veterans Affairs-Boston University-Concussion Legacy Foundation (VA-BU-CLF) Brain Bank between 2008 and 2019. After adjustment for selection bias, college-level and professional football players had 2.38 (95% simulation interval (SI): 1.16, 5.94) and 2.47 (95% SI: 1.46, 4.79) times the risk of being diagnosed with CTE as high-school-level players, respectively; these estimates are larger than estimates with no selection bias adjustment. Since CTE is currently diagnosed only postmortem, we additionally provide plausible scenarios for CTE risk ratios for each level of play during the former players' lifetime. This study provides further evidence to support a dose-response relationship between American football playing and CTE.

Cohort profile: the Liyang cohort study on chronic diseases and risk factors monitoring in China (Liyang Study)

PURPOSE

The Liyang cohort study on chronic diseases and risk factors monitoring in China (Liyang Study) is a prospective population-based study which aims to investigate and identify the determinants of the most prevalent chronic non-communicable diseases (NCDs) and to evaluate the impact of demographic characteristics, lifestyle, dietary habits, cognition, disability and NCDs on the health-related quality of life.

PARTICIPANTS

Between March 2019 and June 2020, 10 056 individuals aged ≥18 years were administered a baseline survey through a multistage cluster random sampling in Liyang City, southern Jiangsu Province, China.

FINDINGS TO DATE

The Liyang Study included detailed sociodemographic, anthropometric and health-related behaviour, common NCDs and blood sample information. Moreover, the study gathered a series of data on specific scales including the activities of daily living, instrumental activities of daily living, abbreviated mental test, Food Frequency Questionnaire and EuroQol 5-Dimensions 5-Levels Scale. Of the 10 056 participants, 52.92% (n=5322) were female and 92.26% (n=9278) came from rural areas. The mean age was 49.9±16.2 years. Men were more likely to have a higher level of education, annual income and a paid job than women (p<0.05). The top three overall most prevalent NCDs in the study were hypertension (18.06%, n=1815), digestive diseases (7.88%, n=791), and arthritis or rheumatism (5.28%, n=530). Women had a significantly higher prevalence of diabetes (5.46%, n=290 vs 4.42%, n=209, p=0.016) and arthritis (6.04%, n=321 vs 4.42%, n=209, p<0.001) than men, while the opposite was true for chronic lung diseases such as chronic obstructive pulmonary disease (1.37%, n=65 vs 0.92%, n=49, p=0.032) and chronic hepatic diseases (0.80%, n=38 vs 0.47%, n=25, p=0.035).

FUTURE PLANS

The current study will give valuable insights into the association between sociodemographic factors, health-related behaviour, diet, cognition, disability and genetic factors and the most prevalent NCDs among local community residents. Starting from 2022, a follow-up survey will be conducted every 3 years to further explore the causal relationship between the above factors and NCDs.

International Travel as a Risk Factor for Carriage of Extended-Spectrum β-Lactamase-Producing Escherichia coli in a Large Sample of European Individuals—The AWARE Study

Antibiotic resistance (AR) is currently a major threat to global health, calling for a One Health approach to be properly understood, monitored, tackled, and managed. Potential risk factors for AR are often studied in specific high-risk populations, but are still poorly understood in the general population. Our aim was to explore, describe, and characterize potential risk factors for carriage of Extended-Spectrum Beta-Lactamase-resistant Escherichia coli (ESBL-EC) in a large sample of European individuals aged between 16 and 67 years recruited from the general population in Southern Germany, the Netherlands, and Romania. Questionnaire and stool sample collection for this cross-sectional study took place from September 2018 to March 2020. Selected cultures of participants’ stool samples were analyzed for detection of ESBL-EC. A total of 1183 participants were included in the analyses: 333 from Germany, 689 from the Netherlands, and 161 from Romania. Travels to Northern Africa (adjusted Odds Ratio, aOR 4.03, 95% Confidence Interval, CI 1.67–9.68), Sub-Saharan Africa (aOR 4.60, 95% CI 1.60–13.26), and Asia (aOR 4.08, 95% CI 1.97–8.43) were identified as independent risk factors for carriage of ESBL-EC. Therefore, travel to these regions should continue to be routinely asked about by clinical practitioners as possible risk factors when considering antibiotic therapy.

Carriage of ESBL-producing Enterobacterales in wastewater treatment plant workers and surrounding residents - the AWARE Study

To investigate whether wastewater treatment plant (WWTP) workers and residents living in close proximity to a WWTP have elevated carriage rates of ESBL-producing Enterobacterales, as compared to the general population. From 2018 to 2020, we carried out a cross-sectional study in Germany, the Netherlands, and Romania among WWTP workers (N = 344), nearby residents (living ≤ 300 m away from WWTPs; N = 431) and distant residents (living ≥ 1000 m away = reference group; N = 1165). We collected information on potential confounders via questionnaire. Culture of participants' stool samples was performed with ChromID®-ESBL agar plates and species identification with MALDI-TOF-MS. We used logistic regression to estimate the odds ratio (OR) for carrying ESBL-producing E. coli (ESBL-EC). Sensitivity analyses included stratification by country and interaction models using country as secondary exposure. Prevalence of ESBL-EC was 11% (workers), 29% (nearby residents), and 7% (distant residents), and higher in Romania (28%) than in Germany (7%) and the Netherlands (6%). Models stratified by country showed that within the Romanian population, WWTP workers are about twice as likely (aOR = 2.34, 95% CI: 1.22-4.50) and nearby residents about three times as likely (aOR = 3.17, 95% CI: 1.80-5.59) to be ESBL-EC carriers, when compared with distant residents. In stratified analyses by country, we found an increased risk for carriage of ESBL-EC in Romanian workers and nearby residents. This effect was higher for nearby residents than for workers, which suggests that, for nearby residents, factors other than the local WWTP could contribute to the increased carriage.

Nature and extent of selection bias resulting from convenience sampling in the emergency department

BACKGROUND

To compare the clinical and demographic variables of patients who present to the ED at different times of the day in order to determine the nature and extent of potential selection bias inherent in convenience sampling METHODS: We undertook a retrospective, observational study of data routinely collected in five EDs in 2019. Adult patients (aged ≥18 years) who presented with abdominal or chest pain, headache or dyspnoea were enrolled. For each patient group, the discharge diagnoses (primary outcome) of patients who presented during the day (08:00-15:59), evening (16:00-23:59), and night (00:00-07:59) were compared. Demographics, triage category and pain score, and initial vital signs were also compared.

RESULTS

2500 patients were enrolled in each of the four patient groups. For patients with abdominal pain, the diagnoses differed significantly across the time periods (p<0.001) with greater proportions of unspecified/unknown cause diagnoses in the evening (47.4%) compared with the morning (41.7%). For patients with chest pain, heart rate differed (p<0.001) with a mean rate higher in the evening (80 beats/minute) than at night (76). For patients with headache, mean patient age differed (p=0.004) with a greater age in the daytime (46 years) than the evening (41). For patients with dyspnoea, discharge diagnoses differed (p<0.001). Asthma diagnoses were more common at night (12.6%) than during the daytime (7.5%). For patients with dyspnoea, there were also differences in gender distribution (p=0.003), age (p<0.001) and respiratory rates (p=0.003) across the time periods. For each patient group, the departure status differed across the time periods (p<0.001).

CONCLUSION

Patients with abdominal or chest pain, headache or dyspnoea differ in a range of clinical and demographic variables depending upon their time of presentation. These differences may potentially introduce selection bias impacting upon the internal validity of a study if convenience sampling of patients is undertaken.

Extension of Mendelian Randomization to Identify Earliest Manifestations of Alzheimer Disease: Association of Genetic Risk Score for Alzheimer Disease With Lower Body Mass Index by Age 50 Years

Weight loss or lower body mass index (BMI) could be an early symptom of Alzheimer disease (AD), but when this begins to emerge is difficult to estimate with traditional observational data. In an extension of Mendelian randomization, we leveraged variation in genetic risk for late-onset AD risk to estimate the causal effect of AD on BMI and the earliest ages at which AD-related weight loss (or lower BMI as a proxy) occurs. We studied UK Biobank participants enrolled in 2006-2010, who were without dementia, aged 39-73, with European genetic ancestry. BMI was calculated with measured height/weight (weight (kg)/height (m)2). An AD genetic risk score (AD-GRS) was calculated based on 23 genetic variants. Using linear regressions, we tested the association of AD-GRS with BMI, stratified by decade, and calculated the age of divergence in BMI trends between low and high AD-GRS. AD-GRS was not associated with BMI in 39- to 49-year-olds (β = 0.00, 95% confidence interval (CI): -0.03, 0.03). AD-GRS was associated with lower BMI in 50- to 59-year-olds (β = -0.03, 95% CI: -0.06, -0.01) and 60- to 73-year-olds (β = -0.09, 95% CI:-0.12, -0.07). Model-based BMI age curves for high versus low AD-GRS began to diverge after age 47 years. Sensitivity analyses found no evidence for pleiotropy or survival bias. Longitudinal replication is needed; however, our findings suggest that AD genes might begin to reduce BMI decades prior to dementia diagnosis.

Inverse probability weighting is an effective method to address selection bias during the analysis of high dimensional data

Omics studies frequently use samples collected during cohort studies. Conditioning on sample availability can cause selection bias if sample availability is nonrandom. Inverse probability weighting (IPW) is purported to reduce this bias. We evaluated IPW in an epigenome-wide analysis testing the association between DNA methylation (261,435 probes) and age in healthy adolescent subjects (n = 114). We simulated age and sex to be correlated with sample selection and then evaluated four conditions: complete population/no selection bias (all subjects), naïve selection bias (no adjustment), and IPW selection bias (selection bias with IPW adjustment). Assuming the complete population condition represented the "truth," we compared each condition to the complete population condition. Bias or difference in associations between age and methylation was reduced in the IPW condition versus the naïve condition. However, genomic inflation and type 1 error were higher in the IPW condition relative to the naïve condition. Postadjustment using bacon, type 1 error and inflation were similar across all conditions. Power was higher under the IPW condition compared with the naïve condition before and after inflation adjustment. IPW methods can reduce bias in genome-wide analyses. Genomic inflation is a potential concern that can be minimized using methods that adjust for inflation.

Application of deep learning to understand resilience to Alzheimer's disease pathology

People who have Alzheimer's disease neuropathologic change (ADNC) typically associated with dementia but not the associated cognitive decline can be considered to be “resilient” to the effects of ADNC. We have previously reported lower neocortical levels of hyperphosphorylated tau (pTau) and less limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC) in the resilient participants compared to those with dementia and similar ADNC as determined by current NIA‐AA recommendations using traditional semi‐quantitative assessments of amyloid β and pathological tau burden. To better understand differences between AD‐dementia and resilient participants, we developed and applied a deep learning approach to analyze the neuropathology of 14 brain donors from the Adult Changes in Thought study, including seven stringently defined resilient participants and seven age‐matched AD‐dementia controls. We created two novel, fully automated deep learning algorithms to quantify the level of phosphorylated TDP‐43 (pTDP‐43) and pTau in whole slide imaging. The models performed better than traditional techniques for quantifying pTDP‐43 and pTau. The second model was able to segment lesions staining for pTau into neurofibrillary tangles (NFTs) and tau neurites (neuronal processes positive for pTau). Both groups had similar quantities of pTau localizing to neurites, but the pTau burden associated with NFTs in the resilient group was significantly lower compared to the group with dementia. These results validate use of deep learning approaches to quantify clinically relevant microscopic characteristics from neuropathology workups. These results also suggest that the burden of NFTs is more strongly associated with cognitive impairment than the more diffuse neuritic tau commonly seen with tangle pathology and suggest that additional factors may underlie resilience mechanisms defined by traditional means.

At-risk-measure Sampling in Case-Control Studies with Aggregated Data

Transient exposures are difficult to measure in epidemiologic studies, especially when both the status of being at risk for an outcome and the exposure change over time and space, as when measuring built-environment risk on transportation injury. Contemporary "big data" generated by mobile sensors can improve measurement of transient exposures. Exposure information generated by these devices typically only samples the experience of the target cohort, so a case-control framework may be useful. However, for anonymity, the data may not be available by individual, precluding a case-crossover approach. We present a method called at-risk-measure sampling. Its goal is to estimate the denominator of an incidence rate ratio (exposed to unexposed measure of the at-risk experience) given an aggregated summary of the at-risk measure from a cohort. Rather than sampling individuals or locations, the method samples the measure of the at-risk experience. Specifically, the method as presented samples person-distance and person-events summarized by location. It is illustrated with data from a mobile app used to record bicycling. The method extends an established case-control sampling principle: sample the at-risk experience of a cohort study such that the sampled exposure distribution approximates that of the cohort. It is distinct from density sampling in that the sample remains in the form of the at-risk measure, which may be continuous, such as person-time or person-distance. This aspect may be both logistically and statistically efficient if such a sample is already available, for example from big-data sources like aggregated mobile-sensor data.

Fine Particulate Matter and Markers of Alzheimer's Disease Neuropathology at Autopsy in a Community-Based Cohort

BACKGROUND

Evidence links fine particulate matter (PM2.5) to Alzheimer's disease (AD), but no community-based prospective cohort studies in older adults have evaluated the association between long-term exposure to PM2.5 and markers of AD neuropathology at autopsy.

OBJECTIVE

Using a well-established autopsy cohort and new spatiotemporal predictions of air pollution, we evaluated associations of 10-year PM2.5 exposure prior to death with Braak stage, Consortium to Establish a Registry for AD (CERAD) score, and combined AD neuropathologic change (ABC score).

METHODS

We used autopsy specimens (N = 832) from the Adult Changes in Thought (ACT) study, with enrollment ongoing since 1994. We assigned long-term exposure at residential address based on two-week average concentrations from a newly developed spatiotemporal model. To account for potential selection bias, we conducted inverse probability weighting. Adjusting for covariates with tiered models, we performed ordinal regression for Braak and CERAD and logistic regression for dichotomized ABC score.

RESULTS

10-year average (SD) PM2.5 from death across the autopsy cohort was 8.2 (1.9) μg/m3. Average age (SD) at death was 89 (7) years. Each 1μg/m3 increase in 10-year average PM2.5 prior to death was associated with a suggestive increase in the odds of worse neuropathology as indicated by CERAD score (OR: 1.35 (0.90, 1.90)) but a suggestive decreased odds of neuropathology as defined by the ABC score (OR: 0.79 (0.49, 1.19)). There was no association with Braak stage (OR: 0.99 (0.64, 1.47)).

CONCLUSION

We report inconclusive associations between PM2.5 and AD neuropathology at autopsy among a cohort where 94% of individuals experienced 10-year exposures below the current EPA standard. Prior studies of AD risk factors and AD neuropathology are similarly inconclusive, suggesting alternative mechanistic pathways for disease or residual confounding.

Characterizing tau deposition in chronic traumatic encephalopathy (CTE): utility of the McKee CTE staging scheme

Chronic traumatic encephalopathy (CTE) is a tauopathy associated with repetitive head impacts (RHI) that has been neuropathologically diagnosed in American football players and other contact sport athletes. In 2013, McKee and colleagues proposed a staging scheme for characterizing the severity of the hyperphosphorylated tau (p-tau) pathology, the McKee CTE staging scheme. The staging scheme defined four pathological stages of CTE, stages I(mild)-IV(severe), based on the density and regional deposition of p-tau. The objective of this study was to test the utility of the McKee CTE staging scheme, and provide a detailed examination of the regional distribution of p-tau in CTE. We examined the relationship between the McKee CTE staging scheme and semi-quantitative and quantitative assessments of regional p-tau pathology, age at death, dementia, and years of American football play among 366 male brain donors neuropathologically diagnosed with CTE (mean age 61.86, SD 18.90). Spearman's rho correlations showed that higher CTE stage was associated with higher scores on all semi-quantitative and quantitative assessments of p-tau severity and density (p's < 0.001). The severity and distribution of CTE p-tau followed an age-dependent progression: older age was associated with increased odds for having a higher CTE stage (p < 0.001). CTE stage was independently associated with increased odds for dementia (p < 0.001). K-medoids cluster analysis of the semi-quantitative scales of p-tau across 14 regions identified 5 clusters of p-tau that conformed to increasing CTE stage (stage IV had 2 slightly different clusters), age at death, dementia, and years of American football play. There was a predilection for p-tau pathology in five regions: dorsolateral frontal cortex (DLF), superior temporal cortex, entorhinal cortex, amygdala, and locus coeruleus (LC), with CTE in the youngest brain donors and lowest CTE stage restricted to DLF and LC. These findings support the usefulness of the McKee CTE staging scheme and demonstrate the regional distribution of p-tau in CTE.

Association of TDP-43 proteinopathy, cerebral amyloid angiopathy, and Lewy bodies with cognitive impairment in individuals with or without Alzheimer's disease neuropathology

Alzheimer's disease patients typically present with multiple co-morbid neuropathologies at autopsy, but the impact of these pathologies on cognitive impairment during life is poorly understood. In this study, we developed cognitive trajectories for patients with common co-pathologies in the presence and absence of Alzheimer's disease neuropathology. Cognitive trajectories were modelled in a Bayesian hierarchical regression framework to estimate the effects of each neuropathology on cognitive decline as assessed by the mini-mental state examination and the clinical dementia rating scale sum of boxes scores. We show that both TDP-43 proteinopathy and cerebral amyloid angiopathy associate with cognitive impairment of similar magnitude to that associated with Alzheimer's disease neuropathology. Within our study population, 63% of individuals given the 'gold-standard' neuropathological diagnosis of Alzheimer's disease in fact possessed either TDP-43 proteinopathy or cerebral amyloid angiopathy of sufficient severity to independently explain the majority of their cognitive impairment. This suggests that many individuals diagnosed with Alzheimer's disease may actually suffer from a mixed dementia, and therapeutics targeting only Alzheimer's disease-related processes may have severely limited efficacy in these co-morbid populations.

Cognitive Resilience to Alzheimer's Disease Pathology in the Human Brain

BACKGROUND

Past research has focused on risk factors for developing dementia, with increasing recognition of "resilient" people who live to old age with intact cognitive function despite pathological features of Alzheimer's disease (AD).

OBJECTIVE

To evaluate demographic factors, mid-life characteristics, and non-AD neuropathology findings that may be associated with cognitive resilience to AD pathology.

METHODS

We analyzed data from 276 autopsy cases with intermediate or high levels of AD pathology from the Adult Changes in Thought study. We defined cognitive resilience as having Cognitive Abilities Screening Instrument scores ≥86 within two years of death and no clinical dementia diagnosis; non-resilient people had dementia diagnoses from AD or other causes before death. We compared mid-life characteristics, demographics, and additional neuropathology findings between resilient and non-resilient people. We used multivariable logistic regression to estimate odds ratios (ORs) with 95% confidence intervals (CIs) for being resilient compared to not being resilient adjusting for demographic and neuropathology factors.

RESULTS

We classified 68 (25%) people as resilient and 208 (75%) as not resilient. A greater proportion of resilient people had a college degree (50%) compared with non-resilient (32%, p = 0.01). The odds of being resilient were significantly increased among people with a college education (OR = 2.01, 95% CI = 1.01-3.99) and significantly reduced among people with additional non-AD neuropathology findings such as hippocampal sclerosis (OR = 0.28, 95% CI = 0.09-0.89) and microinfarcts (OR = 0.34, 95% CI = 0.15-0.78).

CONCLUSION

Increased education and absence of non-AD pathology may be independently associated with cognitive resilience, highlighting the importance of evaluating co-morbid factors in future research on mechanisms of cognitive resilience.

Ophthalmology-Based Neuropathology Risk Factors: Diabetic Retinopathy is Associated with Deep Microinfarcts in a Community-Based Autopsy Study

BACKGROUND

The aging eye offers unique opportunities to study and understand the aging brain, in particular related to Alzheimer's disease (AD) and dementia. However, little is known about relationships between eye diseases and dementia-related neurodegeneration.

OBJECTIVE

To determine the potential association between three age-related eye diseases and AD and dementia-related neuropathology.

METHODS

We reviewed autopsy data from the prospective longitudinal Adult Changes in Thought (ACT) cohort. ICD-9 codes were used to identify diagnoses of diabetic retinopathy, glaucoma, and age-related macular degeneration. Multivariate regression models were used to determine odds ratios (OR) of neuropathology features associated with dementia, including Braak stage, Consortium to Establish a Registry for AD (CERAD score), Lewy bodies, hippocampal sclerosis, and microvascular brain injury, in addition to quantitative paired helical filament (PHF)-tau levels for people with and without each eye condition. We also evaluated interactions between eye conditions and dementia related neuropathologic findings were evaluated.

RESULTS

676 autopsies were included. Diabetic retinopathy was significantly associated with increased risk of deep cerebral microinfarcts (OR = 1.91 [95% confidence interval (CI) 1.11, 3.27], p = 0.02). No other significant association or interaction between eye diseases and neuropathology was found. When PHF-tau quantity was evaluated in 124 decedents, the OR for the association between PHF-tau in the occipital cortex and glaucoma was 1.36 (95% CI 0.91, 2.03, p = 0.13). No statistical correction was made for multiple comparisons.

CONCLUSION

Increased risk of deep cerebral microinfarcts was found in participants diagnosed with diabetic retinopathy. Eye diseases such as glaucoma may increase susceptibility to neurofibrillary tangles in the occipital cortex.

Association Between Sepsis and Microvascular Brain Injury

OBJECTIVES

Many survivors of sepsis suffer long-term cognitive impairment, but the mechanisms of this association remain unknown. The objective of this study was to determine whether sepsis is associated with cerebral microinfarcts on brain autopsy.

DESIGN

Retrospective cohort study.

SETTING AND SUBJECTS

Five-hundred twenty-nine participants of the Adult Changes in Thought, a population-based prospective cohort study of older adults carried out in Kaiser Permanente Washington greater than or equal to 65 years old without dementia at study entry and who underwent brain autopsy.

MEASUREMENTS AND MAIN RESULTS

Late-life sepsis hospitalization was identified using administrative data. We identified 89 individuals with greater than or equal to 1 sepsis hospitalization during study participation, 80 of whom survived hospitalization and died a median of 169 days after discharge. Thirty percent of participants with one or more sepsis hospitalization had greater than two microinfarcts, compared with 19% participants without (χ p = 0.02); 20% of those with sepsis hospitalization had greater than two microinfarcts in the cerebral cortex, compared with 10% of those without (χ p = 0.01). The adjusted relative risk of greater than two microinfarcts was 1.61 (95% CI, 1.01-2.57; p = 0.04); the relative risk for having greater than two microinfarcts in the cerebral cortex was 2.12 (95% CI, 1.12-4.02; p = 0.02). There was no difference in Braak stage for neurofibrillary tangles or consortium to establish a registry for Alzheimer's disease score for neuritic plaques between, but Lewy bodies were less significantly common in those with sepsis.

CONCLUSIONS

Sepsis was specifically associated with moderate to severe vascular brain injury as assessed by microvascular infarcts. This association was stronger for microinfarcts within the cerebral cortex, with those who experienced severe sepsis hospitalization being more than twice as likely to have evidence of moderate to severe cerebral cortical injury in adjusted analyses. Further study to identify mechanisms for the association of sepsis and microinfarcts is needed.

Non-random sampling leads to biased estimates of transcriptome association

Integration of independent data resources across -omics platforms offers transformative opportunity for novel clinical and biological discoveries. However, application of emerging analytic methods in the context of selection bias represents a noteworthy and pervasive challenge. We hypothesize that combining differentially selected samples for integrated transcriptome analysis will lead to bias in the estimated association between predicted expression and the trait. Our results are based on in silico investigations and a case example focused on body mass index across four well-described cohorts apparently derived from markedly different populations. Our findings suggest that integrative analysis can lead to substantial relative bias in the estimate of association between predicted expression and the trait. The average estimate of association ranged from 51.3% less than to 96.7% greater than the true value for the biased sampling scenarios considered, while the average error was - 2.7% for the unbiased scenario. The corresponding 95% confidence interval coverage rate ranged from 46.4% to 69.5% under biased sampling, and was equal to 75% for the unbiased scenario. Inverse probability weighting with observed and estimated weights is applied as one corrective measure and appears to reduce the bias and improve coverage. These results highlight a critical need to address selection bias in integrative analysis and to use caution in interpreting findings in the presence of different sampling mechanisms between groups.

Population-Based Registry Linkages to Improve Validity of Electronic Health Record-Based Cancer Research

BACKGROUND

There is tremendous potential to leverage the value gained from integrating electronic health records (EHR) and population-based cancer registry data for research. Registries provide diagnosis details, tumor characteristics, and treatment summaries, while EHRs contain rich clinical detail. A carefully conducted cancer registry linkage may also be used to improve the internal and external validity of inferences made from EHR-based studies.

METHODS

We linked the EHRs of a large, multispecialty, mixed-payer health care system with the statewide cancer registry and assessed the validity of our linked population. For internal validity, we identify patients that might be "missed" in a linkage, threatening the internal validity of an EHR study population. For generalizability, we compared linked cases with all other cancer patients in the 22-county EHR catchment region.

RESULTS

From an EHR population of 4.5 million, we identified 306,554 patients with cancer, 26% of the catchment region patients with cancer; 22.7% of linked patients were diagnosed with cancer after they migrated away from our health care system highlighting an advantage of system-wide linkage. We observed demographic differences between EHR patients and non-EHR patients in the surrounding region and demonstrated use of selection probabilities with model-based standardization to improve generalizability.

CONCLUSIONS

Our experiences set the foundation to encourage and inform researchers interested in working with EHRs for cancer research as well as provide context for leveraging linkages to assess and improve validity and generalizability.

IMPACT

Researchers conducting linkages may benefit from considering one or more of these approaches to establish and evaluate the validity of their EHR-based populations.See all articles in this CEBP Focus section, "Modernizing Population Science."

Duration of American Football Play and Chronic Traumatic Encephalopathy

OBJECTIVE

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to contact and collision sports, including American football. We hypothesized a dose-response relationship between duration of football played and CTE risk and severity.

METHODS

In a convenience sample of 266 deceased American football players from the Veterans Affairs-Boston University-Concussion Legacy Foundation and Framingham Heart Study Brain Banks, we estimated the association of years of football played with CTE pathological status and severity. We evaluated the ability of years played to classify CTE status using receiver operating characteristic curve analysis. Simulation analyses quantified conditions that might lead to selection bias.

RESULTS

In total, 223 of 266 participants met neuropathological diagnostic criteria for CTE. More years of football played were associated with having CTE (odds ratio [OR] = 1.30 per year played, 95% confidence interval [CI] = 1.19-1.41; p = 3.8 × 10-9 ) and with CTE severity (severe vs mild; OR = 1.14 per year played, 95% CI = 1.07-1.22; p = 3.1 × 10-4 ). Participants with CTE were 1/10th as likely to have played <4.5 years (negative likelihood ratio [LR] = 0.102, 95% CI = 0.100-0.105) and were 10 times as likely to have played >14.5 years (positive LR = 10.2, 95% CI = 9.8-10.7) compared with participants without CTE. Sensitivity and specificity were maximized at 11 years played. Simulation demonstrated that years played remained adversely associated with CTE status when years played and CTE status were both related to brain bank selection across widely ranging scenarios.

INTERPRETATION

The odds of CTE double every 2.6 years of football played. After accounting for brain bank selection, the magnitude of the relationship between years played and CTE status remained consistent. ANN NEUROL 2020;87:116-131.

Mid-life and late-life vascular risk factor burden and neuropathology in old age

OBJECTIVE

To determine whether vascular risk factor burden in mid- or late-life associates with postmortem vascular and neurodegenerative pathologies in a community-based sample.

METHODS

We studied participants from the Framingham Heart Study who participated in our voluntary brain bank program. Overall vascular risk factor burden was calculated using the Framingham Stroke Risk Profile (FSRP). Mid-life FSRP was measured at 50 to 60 years of age. Following death, brains were autopsied and semi-quantitatively assessed by board-certified neuropathologists for cerebrovascular outcomes (cortical infarcts, subcortical infarcts, atherosclerosis, arteriosclerosis) and Alzheimer's disease pathology (Braak stage, cerebral amyloid angiopathy, and neuritic plaque score). We estimated adjusted odds ratios between vascular risk burden (at mid-life and before death) and neuropathological outcomes using logistic and proportional-odds logistic models.

RESULTS

The median time interval between FSRP and death was 33.4 years for mid-life FSRP and 4.4 years for final FSRP measurement before death. Higher mid-life vascular risk burden was associated with increased odds of all cerebrovascular pathology, even with adjustment for vascular risk burden before death. Late-life vascular risk burden was associated with increased odds of cortical infarcts (OR [95% CI]: 1.04 [1.00, 1.08]) and arteriosclerosis stage (OR [95% CI]: 1.03 [1.00, 1.05]). Mid-life vascular risk burden was not associated with Alzheimer's disease pathology, though late-life vascular risk burden was associated with increased odds of higher Braak stage (OR [95% CI]: 1.03 [1.01, 1.05]).

INTERPRETATION

Mid-life vascular risk burden was predictive of cerebrovascular but not Alzheimer's disease neuropathology, even after adjustment for vascular risk factors before death.

Association of White Matter Rarefaction, Arteriolosclerosis, and Tau With Dementia in Chronic Traumatic Encephalopathy

IMPORTANCE

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with repetitive head impacts, including those from US football, that presents with cognitive and neuropsychiatric disturbances that can progress to dementia. Pathways to dementia in CTE are unclear and likely involve tau and nontau pathologic conditions.

OBJECTIVE

To investigate the association of white matter rarefaction and cerebrovascular disease with dementia in deceased men older than 40 years who played football and had CTE.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study involves analyses of data from the ongoing Understanding Neurologic Injury and Traumatic Encephalopathy (UNITE) Study, which is conducted via and included brain donors from the Veterans Affairs-Boston University-Concussion Legacy Foundation brain bank between 2008 and 2017. An original sample of 224 men who had played football and were neuropathologically diagnosed with CTE was reduced after exclusion of those younger than 40 years and those missing data.

EXPOSURES

The number of years of football play as a proxy for repetitive head impacts.

MAIN OUTCOMES AND MEASURES

Neuropathological assessment of white matter rarefaction and arteriolosclerosis severity (on a scale of 0-3, where 3 is severe); number of infarcts, microinfarcts, and microbleeds; and phosphorylated tau accumulation determined by CTE stage and semiquantitative rating of dorsolateral frontal cortex (DLFC) neurofibrillary tangles (NFTs) (none or mild vs moderate or severe). Informant-based retrospective clinical interviews determined dementia diagnoses via diagnostic consensus conferences.

RESULTS

A total of 180 men were included. The mean (SD) age of the sample at death was 67.9 (12.7) years. Of 180, 120 [66.7%]) were found to have had dementia prior to death. Moderate to severe white matter rarefaction (84 of 180 [46.6%]) and arteriolosclerosis (85 of 180 [47.2%]) were common; infarcts, microinfarcts, and microbleeds were not. A simultaneous equations regression model controlling for age and race showed that more years of play was associated with more severe white matter rarefaction (β, 0.16 [95% CI, 0.02-0.29]; P = .03) and greater phosphorylated tau accumulation (DLFC NFTs: β, 0.15 [95% CI, 0.004-0.30]; P = .04; CTE stage: β, 0.27 [95% CI, 0.14-0.41]; P < .001). White matter rarefaction (β, 0.16 [95% CI, 0.02-0.29]; P = .03) and DLFC NFTs (β, 0.16 [95% CI, 0.03-0.28]; P = .01) were associated with dementia. Arteriolosclerosis and years of play were not associated, but arteriolosclerosis was independently associated with dementia (β, 0.21 [95% CI, 0.07-0.35]; P = .003).

CONCLUSIONS AND RELEVANCE

Among older men who had played football and had CTE, more years of football play were associated with more severe white matter rarefaction and greater DLFC NFT burden. White matter rarefaction, arteriolosclerosis, and DLFC NFTs were independently associated with dementia. Dementia in CTE is likely a result of neuropathologic changes, including white matter rarefaction and phosphorylated tau, associated with repetitive head impact and pathologic changes not associated with head trauma, such as arteriolosclerosis.

Exposure to Strong Anticholinergic Medications and Dementia-Related Neuropathology in a Community-Based Autopsy Cohort

BACKGROUND

Anticholinergic medication exposure has been associated with increased risk for dementia. No study has examined the association between anticholinergic medication use and neuropathologic lesions in a community-based sample.

OBJECTIVE

To examine the relationship between anticholinergic exposure and dementia-related neuropathologic changes.

METHODS

Within a community-based autopsy cohort (N = 420), we ascertained use of anticholinergic medications over a 10-year period from automated pharmacy data and calculated total standardized daily doses (TSDD). We used modified Poisson regression to calculate adjusted relative risks (RRs) and 95% confidence intervals (CIs) for the association between anticholinergic exposure and dementia-associated neuropathology. Inverse probability weighting was used to account for selection into the autopsy cohort.

RESULTS

Heavy anticholinergic exposure (≥1,096 TSDD) was not associated with greater neuropathologic changes of Alzheimer's disease; the adjusted RRs for heavy use of anticholinergics (≥1,096 TSDD) compared to no use were 1.22 (95% CI 0.81-1.88) for neuritic plaque scores and 0.89 (0.47-1.66) for extent of neurofibrillary degeneration. Moderate (91-1,095 TSDD) and heavy use of anticholinergics was associated with a significantly lower cerebral microinfarct burden compared with no use with adjusted RRs of 0.44 (0.21-0.89) and 0.24 (0.09-0.62), respectively. Anticholinergic exposure was not associated with macroscopic infarcts or atherosclerosis.

CONCLUSIONS

Use of anticholinergic medications is not associated with Alzheimer's disease-related neuropathologic changes but is associated with lower cerebral microinfarct burden. Further research into biological mechanisms underlying the anticholinergic-dementia link is warranteds.

Age of first exposure to tackle football and chronic traumatic encephalopathy

OBJECTIVE

To examine the effect of age of first exposure to tackle football on chronic traumatic encephalopathy (CTE) pathological severity and age of neurobehavioral symptom onset in tackle football players with neuropathologically confirmed CTE.

METHODS

The sample included 246 tackle football players who donated their brains for neuropathological examination. Two hundred eleven were diagnosed with CTE (126 of 211 were without comorbid neurodegenerative diseases), and 35 were without CTE. Informant interviews ascertained age of first exposure and age of cognitive and behavioral/mood symptom onset.

RESULTS

Analyses accounted for decade and duration of play. Age of exposure was not associated with CTE pathological severity, or Alzheimer's disease or Lewy body pathology. In the 211 participants with CTE, every 1 year younger participants began to play tackle football predicted earlier reported cognitive symptom onset by 2.44 years (p < 0.0001) and behavioral/mood symptoms by 2.50 years (p < 0.0001). Age of exposure before 12 predicted earlier cognitive (p < 0.0001) and behavioral/mood (p < 0.0001) symptom onset by 13.39 and 13.28 years, respectively. In participants with dementia, younger age of exposure corresponded to earlier functional impairment onset. Similar effects were observed in the 126 CTE-only participants. Effect sizes were comparable in participants without CTE.

INTERPRETATION

In this sample of deceased tackle football players, younger age of exposure to tackle football was not associated with CTE pathological severity, but predicted earlier neurobehavioral symptom onset. Youth exposure to tackle football may reduce resiliency to late-life neuropathology. These findings may not generalize to the broader tackle football population, and informant-report may have affected the accuracy of the estimated effects. Ann Neurol 2018;83:886-901.

Youth Exposure to Repetitive Head Impacts From Tackle Football and Long-term Neurologic Outcomes: A Review of the Literature, Knowledge Gaps and Future Directions, and Societal and Clinical Implications

Youth participation in contact and collision sports, particularly tackle football, is associated with exposure to repetitive head impacts during a time period when tremendous brain maturation is occurring. Accumulating evidence suggests that exposure to repetitive head impacts from youth tackle football may increase vulnerability to long-term cognitive, neuropsychiatric, and neurologic disturbances. There are limitations to the current literature and conflicting findings exist. Nonetheless, participation in youth football has become a cause of concern to clinicians, scientists, politicians, coaches, parents, and children. The objective of this paper is to review the literature on the long-term cognitive, neuropsychiatric, and neurologic outcomes associated with participation in youth contact and collision sports, with a focus on tackle football. We provide an overview of the empirically derived framework that has served as the foundation for the investigation of youth tackle football and neurologic outcomes. The extant research studies on age of first exposure to tackle football and later-life cognitive and neuropsychiatric functioning, as well as structural brain changes are reviewed. We discuss the limitations of the current evidence, suggest future directions, and conclude with our opinions on societal and clinical implications.

Reflection on modern methods: selection bias-a review of recent developments

Selection bias remains a more difficult bias to understand than confounding or measurement error. Past definitions have not always been illuminating and a simple method (such as the change-in-estimate method for confounding) has not been available to determine its presence and magnitude in the study sample. A better understanding of the nature of the bias has led to the definition of endogenous selection bias. It is the result of conditioning on a collider variable, itself caused by two other variables; the latter variables become spuriously associated. Conditioning on a variable in the analysis that is a collider or on an indicator of sample selection has the same effect. Note that selection bias is possible even in the absence of a collider, but in the presence of endogenous selection bias, the concern is whether it is possible to identify a causal effect in the sample. Conditions have been outlined to determine that. However, even if conditions are met to identify a causal effect in the study sample, its generalization to a defined target population is not a given.We discuss the concept of endogeneity and the sources of endogenous selection bias in observational studies. We then briefly address the terms generalizability, target population (or alternative formulations) and transportability. We outline the explicit conditions to identify causal effects in studies affected by selection bias: they involve exchangeability between exposed and unexposed and exchangeability between sampled and unsampled. We briefly describe methods to generalize estimated causal effects to the target population. The latter usually require data from the target population. Finally we discuss sensitivity analyses; some are limited to providing an indication of the presence and direction of the bias and others can provide corrected estimates with user-supplied selection bias parameters.

Associations between Use of Specific Analgesics and Concentrations of Amyloid-β 42 or Phospho-Tau in Regions of Human Cerebral Cortex

Analgesics are commonly used by older adults, raising the question of whether their use might contribute to dementia risk and neuropathologic changes of Alzheimer's disease (AD). The Adult Changes in Thought (ACT) study is a population-based study of brain aging and incident dementia among people 65 years or older who are community dwelling and not demented at entry. Amyloid-β (Aβ)42 and phospho-tau were quantified using Histelide in regions of cerebral cortex from 420 brain autopsies. Total standard daily doses of prescription opioid and non-aspirin nonsteroidal anti-inflammatory drug (NSAID) exposure during a defined 10-year exposure window were identified using automated pharmacy dispensing data and used to classify people as having no/low, intermediate, or high exposure. People with high NSAID exposure had significantly greater Aβ42 concentration in middle frontal gyrus and superior and middle temporal gyri, but not inferior parietal lobule; no Aβ42 regional concentration was associated with prescription opioid usage. People with high opioid usage had significantly greater concentration of phospho-tau in middle frontal gyrus than people with little-to-no opioid usage. Consistent with our previous studies, findings suggest that high levels of NSAID use in older individuals may promote Aβ42 accumulation in cerebral cortex.

Use of Analgesics (Opioids and Nonsteroidal Anti-Inflammatory Drugs) and Dementia-Related Neuropathology in a Community-Based Autopsy Cohort

BACKGROUND

Opioids may influence the development of Alzheimer's disease (AD). Some studies have observed AD pathology in the brains of opioid abusers. No study has examined the association between prescription opioid use and dementia-related neuropathologic changes.

OBJECTIVE

To examine the relationship between prescription opioid or NSAID use and dementia-related neuropathologic changes.

METHODS

Within a community-based autopsy cohort (N = 420), we ascertained opioid and nonsteroidal anti-inflammatory drug (NSAID) use over a 10-year period from automated pharmacy data and calculated total standardized daily doses (TSDDs). A neuropathologist assessed outcomes including neuritic plaques, neurofibrillary tangles, and macroscopic infarcts. Outcome measures were dichotomized using established cutpoints. We used modified Poisson regression to calculate adjusted relative risks (RR) and 95% confidence intervals (CI), accounting for participant characteristics and using weighting to account for possible selection bias related to selection into the autopsy sample.

RESULTS

Heavier opioid exposure was not associated with greater neuropathologic changes. For neuritic plaques, the adjusted RR [95% CI] was 0.99 [0.64-1.47] for 91+ TSDDs of opioids versus little to no use, and for neurofibrillary tangles, 0.97 [0.49-1.78]. People with heavy NSAID use had higher risk of neuritic plaques (RR 1.39 [1.01-1.89]) than those with little to no use, as we have previously reported. Neither opioid nor NSAID use was associated with higher risk of macroscopic infarcts or with Lewy body disease.

CONCLUSION

Prescription opioid use is not associated with dementia-related neuropathologic changes, but heavy NSAID use may be. More research is needed examining chronic pain, its pharmacologic treatments, and neuropathologic changes.

Assessing robustness of hazard ratio estimates to outcome misclassification in longitudinal panel studies with application to Alzheimer's disease

Analyses of imperfectly assessed time to event outcomes give rise to biased hazard ratio estimates. This bias is a common challenge for studies of Alzheimer’s Disease (AD) because AD neuropathology can only be identified through brain autopsy and is therefore not available for most study participants. Clinical AD diagnosis, although more widely available, has imperfect sensitivity and specificity relative to AD neuropathology. In this study we present a sensitivity analysis approach using a bias-adjusted discrete proportional hazards model to quantify robustness of results to misclassification of a time to event outcome and apply this method to data from a longitudinal panel study of AD. Using data on 1,955 participants from the Adult Changes in Thought study we analyzed the association between average glucose level and AD neuropathology and conducted sensitivity analyses to explore how estimated hazard ratios varied according to AD classification accuracy. Unadjusted hazard ratios were closer to the null than estimates obtained under most scenarios for misclassification investigated. Confidence interval estimates from the unadjusted model were substantially underestimated compared to adjusted estimates. This study demonstrates the importance of exploring outcome misclassification in time to event analyses and provides an approach that can be undertaken without requiring validation data.

Regional brain morphometry in patients with traumatic brain injury based on acute- and chronic-phase magnetic resonance imaging

Traumatic brain injury (TBI) is caused by a sudden external force and can be very heterogeneous in its manifestation. In this work, we analyse T1-weighted magnetic resonance (MR) brain images that were prospectively acquired from patients who sustained mild to severe TBI. We investigate the potential of a recently proposed automatic segmentation method to support the outcome prediction of TBI. Specifically, we extract meaningful cross-sectional and longitudinal measurements from acute- and chronic-phase MR images. We calculate regional volume and asymmetry features at the acute/subacute stage of the injury (median: 19 days after injury), to predict the disability outcome of 67 patients at the chronic disease stage (median: 229 days after injury). Our results indicate that small structural volumes in the acute stage (e.g. of the hippocampus, accumbens, amygdala) can be strong predictors for unfavourable disease outcome. Further, group differences in atrophy are investigated. We find that patients with unfavourable outcome show increased atrophy. Among patients with severe disability outcome we observed a significantly higher mean reduction of cerebral white matter (3.1%) as compared to patients with low disability outcome (0.7%).

Neuropathological and transcriptomic characteristics of the aged brain

As more people live longer, age-related neurodegenerative diseases are an increasingly important societal health issue. Treatments targeting specific pathologies such as amyloid beta in Alzheimer’s disease (AD) have not led to effective treatments, and there is increasing evidence of a disconnect between traditional pathology and cognitive abilities with advancing age, indicative of individual variation in resilience to pathology. Here, we generated a comprehensive neuropathological, molecular, and transcriptomic characterization of hippocampus and two regions cortex in 107 aged donors (median = 90) from the Adult Changes in Thought (ACT) study as a freely-available resource (http://aging.brain-map.org/). We confirm established associations between AD pathology and dementia, albeit with increased, presumably aging-related variability, and identify sets of co-expressed genes correlated with pathological tau and inflammation markers. Finally, we demonstrate a relationship between dementia and RNA quality, and find common gene signatures, highlighting the importance of properly controlling for RNA quality when studying dementia.

Modeling the Relationships Among Late-Life Body Mass Index, Cerebrovascular Disease, and Alzheimer's Disease Neuropathology in an Autopsy Sample of 1,421 Subjects from the National Alzheimer's Coordinating Center Data Set

The relationship between late-life body mass index (BMI) and Alzheimer's disease (AD) is poorly understood due to the lack of research in samples with autopsy-confirmed AD neuropathology (ADNP). The role of cerebrovascular disease (CVD) in the interplay between late-life BMI and ADNP is unclear. We conducted a retrospective longitudinal investigation and used joint modeling of linear mixed effects to investigate causal relationships among repeated antemortem BMI measurements, CVD (quantified neuropathologically), and ADNP in an autopsy sample of subjects across the AD clinical continuum. The sample included 1,421 subjects from the National Alzheimer's Coordinating Center's Uniform Data Set and Neuropathology Data Set with diagnoses of normal cognition (NC; n = 234), mild cognitive impairment (MCI; n = 201), or AD dementia (n = 986). ADNP was defined as moderate to frequent neuritic plaques and Braak stageIII-VI. Ischemic Injury Scale (IIS) operationalized CVD. Joint modeling examined relationships among BMI, IIS, and ADNP in the overall sample and stratified by initial visit Clinical Dementia Rating score. Subject-specific random intercept for BMI was the predictor for ADNP due to minimal BMI change (p = 0.3028). Analyses controlling for demographic variables and APOE ɛ4 showed lower late-life BMI predicted increased odds of ADNP in the overall sample (p < 0.001), and in subjects with CDR of 0 (p = 0.0021) and 0.5 (p = 0.0012), but not ≥1.0 (p = 0.2012). Although higher IIS predicted greater odds of ADNP (p < 0.0001), BMI did not predict IIS (p = 0.2814). The current findings confirm lower late-life BMI confers increased odds for ADNP. Lower late-life BMI may be a preclinical indicator of underlying ADNP.

Evaluating disease prediction models using a cohort whose covariate distribution differs from that of the target population

Personal predictive models for disease development play important roles in chronic disease prevention. The performance of these models is evaluated by applying them to the baseline covariates of participants in external cohort studies, with model predictions compared to subjects' subsequent disease incidence. However, the covariate distribution among participants in a validation cohort may differ from that of the population for which the model will be used. Since estimates of predictive model performance depend on the distribution of covariates among the subjects to which it is applied, such differences can cause misleading estimates of model performance in the target population. We propose a method for addressing this problem by weighting the cohort subjects to make their covariate distribution better match that of the target population. Simulations show that the method provides accurate estimates of model performance in the target population, while un-weighted estimates may not. We illustrate the method by applying it to evaluate an ovarian cancer prediction model targeted to US women, using cohort data from participants in the California Teachers Study. The methods can be implemented using open-source code for public use as the R-package RMAP (Risk Model Assessment Package) available at http://stanford.edu/~ggong/rmap/ .

Clinicopathological Evaluation of Chronic Traumatic Encephalopathy in Players of American Football

IMPORTANCE

Players of American football may be at increased risk of long-term neurological conditions, particularly chronic traumatic encephalopathy (CTE).

OBJECTIVE

To determine the neuropathological and clinical features of deceased football players with CTE.

DESIGN, SETTING, AND PARTICIPANTS

Case series of 202 football players whose brains were donated for research. Neuropathological evaluations and retrospective telephone clinical assessments (including head trauma history) with informants were performed blinded. Online questionnaires ascertained athletic and military history.

EXPOSURES

Participation in American football at any level of play.

MAIN OUTCOMES AND MEASURES

Neuropathological diagnoses of neurodegenerative diseases, including CTE, based on defined diagnostic criteria; CTE neuropathological severity (stages I to IV or dichotomized into mild [stages I and II] and severe [stages III and IV]); informant-reported athletic history and, for players who died in 2014 or later, clinical presentation, including behavior, mood, and cognitive symptoms and dementia.

RESULTS

Among 202 deceased former football players (median age at death, 66 years [interquartile range, 47-76 years]), CTE was neuropathologically diagnosed in 177 players (87%; median age at death, 67 years [interquartile range, 52-77 years]; mean years of football participation, 15.1 [SD, 5.2]), including 0 of 2 pre-high school, 3 of 14 high school (21%), 48 of 53 college (91%), 9 of 14 semiprofessional (64%), 7 of 8 Canadian Football League (88%), and 110 of 111 National Football League (99%) players. Neuropathological severity of CTE was distributed across the highest level of play, with all 3 former high school players having mild pathology and the majority of former college (27 [56%]), semiprofessional (5 [56%]), and professional (101 [86%]) players having severe pathology. Among 27 participants with mild CTE pathology, 26 (96%) had behavioral or mood symptoms or both, 23 (85%) had cognitive symptoms, and 9 (33%) had signs of dementia. Among 84 participants with severe CTE pathology, 75 (89%) had behavioral or mood symptoms or both, 80 (95%) had cognitive symptoms, and 71 (85%) had signs of dementia.

CONCLUSIONS AND RELEVANCE

In a convenience sample of deceased football players who donated their brains for research, a high proportion had neuropathological evidence of CTE, suggesting that CTE may be related to prior participation in football.

A novel association test for multiple secondary phenotypes from a case-control GWAS

In the past decade, many genome-wide association studies (GWASs) have been conducted to explore association of single nucleotide polymorphisms (SNPs) with complex diseases using a case-control design. These GWASs not only collect information on the disease status (primary phenotype, D) and the SNPs (genotypes, X), but also collect extensive data on several risk factors and traits. Recent literature and grant proposals point toward a trend in reusing existing large case-control data for exploring genetic associations of some additional traits (secondary phenotypes, Y) collected during the study. These secondary phenotypes may be correlated, and a proper analysis warrants a multivariate approach. Commonly used multivariate methods are not equipped to properly account for the non-random sampling scheme. Current ad hoc practices include analyses without any adjustment, and analyses with D adjusted as a covariate. Our theoretical and empirical studies suggest that the type I error for testing genetic association of secondary traits can be substantial when X as well as Y are associated with D, even when there is no association between X and Y in the underlying (target) population. Whether using D as a covariate helps maintain type I error depends heavily on the disease mechanism and the underlying causal structure (which is often unknown). To avoid grossly incorrect inference, we have proposed proportional odds model adjusted for propensity score (POM-PS). It uses a proportional odds logistic regression of X on Y and adjusts estimated conditional probability of being diseased as a covariate. We demonstrate the validity and advantage of POM-PS, and compare to some existing methods in extensive simulation experiments mimicking plausible scenarios of dependency among Y, X, and D. Finally, we use POM-PS to jointly analyze four adiposity traits using a type 2 diabetes (T2D) case-control sample from the population-based Metabolic Syndrome in Men (METSIM) study. Only POM-PS analysis of the T2D case-control sample seems to provide valid association signals.

Outcomes after diagnosis of mild cognitive impairment in a large autopsy series

OBJECTIVE

To determine clinical and neuropathological outcomes following a clinical diagnosis of mild cognitive impairment (MCI).

METHODS

Data were drawn from a large autopsy series (N = 1,337) of individuals followed longitudinally from normal or MCI status to death, derived from 4 Alzheimer Disease (AD) Centers in the United States.

RESULTS

Mean follow-up was 7.9 years. Of the 874 individuals ever diagnosed with MCI, final clinical diagnoses were varied: 39.2% died with an MCI diagnosis, 46.8% with a dementia diagnosis, and 13.9% with a diagnosis of intact cognition. The latter group had pathological features resembling those with a final clinical diagnosis of MCI. In terms of non-AD pathologies, both primary age-related tauopathy (p < 0.05) and brain arteriolosclerosis pathology (p < 0.001) were more severe in MCI than cognitively intact controls. Among the group that remained MCI until death, mixed AD neuropathologic changes (ADNC; ≥1 comorbid pathology) were more frequent than "pure" ADNC pathology (55% vs 22%); suspected non-Alzheimer pathology comprised the remaining 22% of cases. A majority (74%) of subjects who died with MCI were without "high"-level ADNC, Lewy body disease, or hippocampal sclerosis pathologies; this group was enriched in cerebrovascular pathologies. Subjects who died with dementia and were without severe neurodegenerative pathologies tended to have cerebrovascular pathology and carry the MCI diagnosis for a longer interval.

INTERPRETATION

MCI diagnosis usually was associated with comorbid neuropathologies; less than one-quarter of MCI cases showed "pure" AD at autopsy. Ann Neurol 2017;81:549-559.

Alzheimer's disease neuropathologic change, Lewy body disease, and vascular brain injury in clinic- and community-based samples

We examined the relationships between Alzheimer's disease neuropathologic change (ADNC), Lewy body disease (LBD), and vascular brain injury (VBI) in 2 large autopsy samples. Because findings may differ between study populations, data came from U.S. Alzheimer's Disease Centers contributing to the National Alzheimer's Coordinating Center (n = 2742) and from the population-based Adult Changes in Thought study (n = 499). Regardless of study population, over 50% of participants with ADNC had co-occurring LBD or VBI; the majority of whom had a clinical AD dementia diagnosis prior to death. Overlap of pathologies was similar between studies, especially after standardizing to the distribution of age and dementia status in the Adult Changes in Thought population. LBD, but not VBI, was positively associated with ADNC in both studies. Interestingly, cortical LBD was more common in those with intermediate ADNC compared to low or high ADNC, especially in the National Alzheimer's Coordinating Center (p < 0.001). High prevalence of co-occurring neuropathologies among older adults with dementia has implications for accurate diagnosis of dementia etiologies and development of disease-modifying strategies.