Assessing Dementia Prevalence in the Wisconsin Longitudinal Study: Cohort Profile, Protocol, and Preliminary Findings.

BACKGROUND: There is growing consensus that non-genetic determinants of dementia can be linked to various risk- and resiliency-enhancing factors accumulating throughout the lifespan, including socioeconomic conditions, early life experiences, educational attainment, lifestyle behaviors, and physical/mental health. Yet, the causal impact of these diverse factors on dementia risk remain poorly understood due to few longitudinal studies prospectively characterizing these influences across the lifespan. OBJECTIVE: The Initial Lifespan's Impact on Alzheimer's Disease and Related Dementia (ILIAD) study aims to characterize dementia prevalence in the Wisconsin Longitudinal Study (WLS), a 60-year longitudinal study documenting life course trajectories of educational, family, occupational, psychological, cognitive, and health measures. METHODS: Participants are surveyed using the modified Telephone Interview for Cognitive Status (TICS-m) to identify dementia risk. Those scoring below cutoff undergo home-based neuropsychological, physical/neurological, and functional assessments. Dementia diagnosis is determined by consensus panel and merged with existing WLS data for combined analysis. RESULTS: Preliminary findings demonstrate the initial success of the ILIAD protocol in detecting dementia prevalence in the WLS. Increasing age, hearing issues, lower IQ, male sex, APOE4 positivity, and a steeper annualized rate of memory decline assessed in the prior two study waves, all increased likelihood of falling below the TICS-m cutoff for dementia risk. TICS-m scores significantly correlated with standard neuropsychological performance and functional outcomes. CONCLUSION: We provide an overview of the WLS study, describe existing key lifespan variables relevant to studies of dementia and cognitive aging, detail the current WLS-ILIAD study protocol, and provide a first glimpse of preliminary study findings.

Personality Predicts Mortality Risk: An Integrative Data Analysis of 15 International Longitudinal Studies.

This study examined the Big Five personality traits as predictors of mortality risk, and smoking as a mediator of that association. Replication was built into the fabric of our design: we used a Coordinated Analysis with 15 international datasets, representing 44,094 participants. We found that high neuroticism and low conscientiousness, extraversion, and agreeableness were consistent predictors of mortality across studies. Smoking had a small mediating effect for neuroticism. Country and baseline age explained variation in effects: studies with older baseline age showed a pattern of protective effects (HR<1.00) for openness, and U.S. studies showed a pattern of protective effects for extraversion. This study demonstrated coordinated analysis as a powerful approach to enhance replicability and reproducibility, especially for aging-related longitudinal research.

Association of Playing High School Football With Cognition and Mental Health Later in Life.

Importance: American football is the largest participation sport in US high schools and is a leading cause of concussion among adolescents. Little is known about the long-term cognitive and mental health consequences of exposure to football-related head trauma at the high school level. Objective: To estimate the association of playing high school football with cognitive impairment and depression at 65 years of age. Design, Setting, and Participants: A representative sample of male high school students who graduated from high school in Wisconsin in 1957 was studied. In this cohort study using data from the Wisconsin Longitudinal Study, football players were matched between March 1 and July 1, 2017, with controls along several baseline covariates such as adolescent IQ, family background, and educational level. For robustness, 3 versions of the control condition were considered: all controls, those who played a noncollision sport, and those who did not play any sport. Exposures: Athletic participation in high school football. Main Outcomes and Measures: A composite cognition measure of verbal fluency and memory and attention constructed from results of cognitive assessments administered at 65 years of age. A modified Center for Epidemiological Studies' Depression Scale score was used to measure depression. Secondary outcomes include results of individual cognitive tests, anger, anxiety, hostility, and heavy use of alcohol. Results: Among the 3904 men (mean [SD] age, 64.4 [0.8] years at time of primary outcome measurement) in the study, after matching and model-based covariate adjustment, compared with each control condition, there was no statistically significant harmful association of playing football with a reduced composite cognition score (-0.04 reduction in cognition vs all controls; 97.5% CI, -0.14 to 0.05) or an increased modified Center for Epidemiological Studies' Depression Scale depression score (-1.75 reduction vs all controls; 97.5% CI, -3.24 to -0.26). After adjustment for multiple testing, playing football did not have a significant adverse association with any of the secondary outcomes, such as the likelihood of heavy alcohol use at 65 years of age (odds ratio, 0.68; 95% CI, 0.32-1.43). Conclusions and Relevance: Cognitive and depression outcomes later in life were found to be similar for high school football players and their nonplaying counterparts from mid-1950s in Wisconsin. The risks of playing football today might be different than in the 1950s, but for current athletes, this study provides information on the risk of playing sports today that have a similar risk of head trauma as high school football played in the 1950s.

The Influence of Social Conditions Across the Life Course on the Human Gut Microbiota: A Pilot Project With the Wisconsin Longitudinal Study.

Objective: To test the feasibility of collecting and integrating data on the gut microbiome into one of the most comprehensive longitudinal studies of aging and health, the Wisconsin Longitudinal Study (WLS). The long-term goal of this integration is to clarify the contribution of social conditions in shaping the composition of the gut microbiota late in life. Research on the microbiome, which is considered to be of parallel importance to human health as the human genome, has been hindered by human studies with nonrandomly selected samples and with limited data on social conditions over the life course. Methods: No existing population-based longitudinal study had collected fecal specimens. Consequently, we created an in-person protocol to collect stool specimens from a subgroup of WLS participants. Results: We collected 429 stool specimens, yielding a 74% response rate and one of the largest human samples to date. Discussion: The addition of data on the gut microbiome to the WLS-and to other population based longitudinal studies of aging-is feasible, under the right conditions, and can generate innovative research on the relationship between social conditions and the gut microbiome.

Myocardial infarction in the Wisconsin Longitudinal Study: the interaction among environmental, health, social, behavioural and genetic factors.

OBJECTIVES: This study examined how environmental, health, social, behavioural and genetic factors interact to contribute to myocardial infarction (MI) risk. DESIGN: Survey data collected by Wisconsin Longitudinal Study (WLS), USA, from 1957 to 2011, including 235 environmental, health, social and behavioural factors, and 77 single- nucleotide polymorphisms were analysed for association with MI. To identify associations with MI we utilized recursive partitioning and random forest prior to logistic regression and chi-squared analyses. PARTICIPANTS: 6198 WLS participants (2938 men; 3260 women) who (1) had a MI before 72 years and (2) had a MI between 65 and 72 years. RESULTS: In men, stroke (LR OR: 5.01, 95% CI 3.36 to 7.48), high cholesterol (3.29, 2.59 to 4.18), diabetes (3.24, 2.53 to 4.15) and high blood pressure (2.39, 1.92 to 2.96) were significantly associated with MI up to 72 years of age. For those with high cholesterol, the interaction of smoking and lower alcohol consumption increased prevalence from 23% to 41%, with exposure to dangerous working conditions, a factor not previously linked with MI, further increasing prevalence to 50%. Conversely, MI was reported in <2.5% of men with normal cholesterol and no history of diabetes or depression. Only stroke (4.08, 2.17 to 7.65) and diabetes (2.71, 1.81 to 4.04) by 65 remained significantly associated with MI for men after age 65. For women, diabetes (5.62, 4.08 to 7.75), high blood pressure (3.21, 2.34 to 4.39), high cholesterol (2.03, 1.38 to 3.00) and dissatisfaction with their financial situation (4.00, 1.94 to 8.27) were significantly associated with MI up to 72 years of age. Conversely, often engaging in physical activity alone (0.53, 0.32 to 0.89) or with others (0.34, 0.21 to 0.57) was associated with the largest reduction in odds of MI. Being non-diabetic with normal blood pressure and engaging in physical activity often lowered prevalence of MI to 0.2%. Only diabetes by 65 (4.25, 2.50 to 7.24) and being exposed to dangerous work conditions at 54 (2.24, 1.36 to 3.69) remained significantly associated with MI for women after age 65, while still menstruating at 54 (0.46, 0.23 to 0.91) was associated with reduced odds of MI. CONCLUSIONS: Together these results indicate important differences in factors associated with MI between the sexes, that combinations of factors greatly influence the likelihood of MI, that MI-associated factors change and associations weaken after 65 years of age in both sexes, and that the limited genotypes assessed were secondary to environmental, health, social and behavioral factors.

Cohort profile: Wisconsin longitudinal study (WLS).

The Wisconsin Longitudinal Study (WLS) is a longitudinal study of men and women who graduated from Wisconsin high schools in 1957 and one of their randomly selected siblings. Wisconsin is located in the upper midwest of the United States and had a population of approximately 14 000 000 in 1957, making it the 14th most populous state at that time. Data spanning almost 60 years allow researchers to link family background, adolescent characteristics, educational experiences, employment experiences, income, wealth, family formation and social and religious engagement to midlife and late-life physical health, mental health, psychological well-being, cognition, end of life planning and mortality. The WLS is one of the few longitudinal data sets that include an administrative measure of cognition from childhood. Further, recently collected saliva samples allow researchers to explore the inter-relationships among genes, behaviours and environment, including genetic determinants of behaviours (e.g. educational attainment); the interactions between genes and environment; and how these interactions predict behaviours. Most panel members were born in 1939, and the sample is broadly representative of White, non-Hispanic American men and women who have completed at least a high school education. Siblings cover several adjoining cohorts: they were born primarily between 1930 and 1948. At each interview, about two-thirds of the sample lived in Wisconsin, and about one-third lived elsewhere in the United States or abroad. The data, along with documentation, are publicly accessible and can be accessed at http://www.ssc.wisc.edu/wlsresearch/. Requests for protected data or assistance should be sent to wls@ssc.wisc.edu.

Assessment of genetic and nongenetic interactions for the prediction of depressive symptomatology: an analysis of the Wisconsin Longitudinal Study using machine learning algorithms.

OBJECTIVES: We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. METHODS: We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors-13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors-18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. RESULTS: After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. CONCLUSIONS: We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic-environmental-sociobehavioral interactions in depressive symptoms.

Multigene interactions and the prediction of depression in the Wisconsin Longitudinal Study.

OBJECTIVES: Single genetic loci offer little predictive power for the identification of depression. This study examined whether an analysis of gene-gene (G × G) interactions of 78 single nucleotide polymorphisms (SNPs) in genes associated with depression and age-related diseases would identify significant interactions with increased predictive power for depression. DESIGN: A retrospective cohort study. SETTING: A survey of participants in the Wisconsin Longitudinal Study. PARTICIPANTS: A total of 4811 persons (2464 women and 2347 men) who provided saliva for genotyping; the group comes from a randomly selected sample of Wisconsin high school graduates from the class of 1957 as well as a randomly selected sibling, almost all of whom are non-Hispanic white. PRIMARY OUTCOME MEASURE: Depression as determine by the Composite International Diagnostic Interview-Short-Form. RESULTS: Using a classification tree approach (recursive partitioning (RP)), the authors identified a number of candidate G × G interactions associated with depression. The primary SNP splits revealed by RP (ANKK1 rs1800497 (also known as DRD2 Taq1A) in men and DRD2 rs224592 in women) were found to be significant as single factors by logistic regression (LR) after controlling for multiple testing (p=0.001 for both). Without considering interaction effects, only one of the five subsequent RP splits reached nominal significance in LR (FTO rs1421085 in women, p=0.008). However, after controlling for G × G interactions by running LR on RP-specific subsets, every split became significant and grew larger in magnitude (OR (before) → (after): men: GNRH1 novel SNP: (1.43 → 1.57); women: APOC3 rs2854116: (1.28 → 1.55), ACVR2B rs3749386: (1.11 → 2.17), FTO rs1421085: (1.32 → 1.65), IL6 rs1800795: (1.12 → 1.85)). CONCLUSIONS: The results suggest that examining G × G interactions improves the identification of genetic associations predictive of depression. 4 of the SNPs identified in these interactions were located in two pathways well known to impact depression: neurotransmitter (ANKK1 and DRD2) and neuroendocrine (GNRH1 and ACVR2B) signalling. This study demonstrates the utility of RP analysis as an efficient and powerful exploratory analysis technique for uncovering genetic and molecular pathway interactions associated with disease aetiology.