Digitally generated Trail Making Test data: Analysis using hidden Markov modeling.

The Trail Making Test (TMT) is a neuropsychological test used to assess cognitive dysfunction. The TMT consists of two parts: TMT-A requires connecting numbers 1 to 25 sequentially; TMT-B requires connecting numbers 1 to 12 and letters A to L sequentially, alternating between numbers and letters. We propose using a digitally recorded version of TMT to capture cognitive or physical functions underlying test performance. We analyzed digital versions of TMT-A and -B to derive time metrics and used Bayesian hidden Markov models to extract additional metrics. We correlated these derived metrics with cognitive and physical function scores using regression. On both TMT-A and -B, digital metrics associated with graphomotor processing test scores and gait speed. Digital metrics on TMT-B were additionally associated with episodic memory test scores and grip strength. These metrics provide additional information of cognitive state and can differentiate cognitive and physical factors affecting test performance.

Slower Decline in Processing Speed Is Associated with Familial Longevity.

INTRODUCTION: Cross-sectional analyses have associated familial longevity with better cognitive function and lower risk of cognitive impairment in comparison with individuals without familial longevity. The extent to which long-lived families also demonstrate slower rates of cognitive aging (i.e., change in cognition over time) is unknown. This study examined longitudinally collected data among 2 generations of the Long Life Family Study (LLFS) to compare rates of cognitive change across relatives and spouse controls. METHODS: We analyzed change in 6 neuropsychological test scores collected approximately 8 years apart among LLFS family members (n = 3,972) versus spouse controls (n = 1,092) using a Bayesian hierarchical model that included age, years of follow-up, sex, education, generation, and field center and all possible pairwise interactions. RESULTS: At a mean age of 88 years at enrollment in the older generation and 60 years in the younger generation, LLFS family members performed better than their spouses on the Digit Symbol Substitution Test (DSST) and the Logical Memory test. At follow-up, family members in the younger generation also showed slower decline than spouses on the DSST, whereas rates of change of Digit Span, fluency, and memory were similar between the 2 groups. DISCUSSION/CONCLUSION: Individuals in families with longevity appear to have better cognitive performance than their spouses for cognitive processes including psychomotor processing, episodic memory, and retrieval. Additionally, they demonstrate longer cognitive health spans with a slower decline on a multifactorial test of processing speed, a task requiring the integration of processes including organized visual search, working and incidental memory, and graphomotor ability. Long-lived families may be a valuable cohort for studying resilience to cognitive aging.

Association Between APOE Alleles and Change of Neuropsychological Tests in the Long Life Family Study.

BACKGROUND: The Long Life Family Study (LLFS) is a family based, prospective study of healthy aging and familial longevity. The study includes two assessments of cognitive function that were administered approximately 8 years apart. OBJECTIVE: To test whether APOE genotype is associated with change of cognitive function in older adults. METHODS: We used Bayesian hierarchical models to test the association between APOE alleles and change of cognitive function. Six longitudinally collected neuropsychological test scores were modelled as a function of age at enrollment, follow-up time, gender, education, field center, birth cohort indicator (≤1935, or >1935), and the number of copies of ɛ2 or ɛ4 alleles. RESULTS: Out of 4,587 eligible participants, 2,064 were male (45.0%), and age at enrollment ranged from 25 to 110 years, with mean of 70.85 years (SD: 15.75). We detected a significant cross-sectional effect of the APOEɛ4 allele on Logical Memory. Participants carrying at least one copy of the ɛ4 allele had lower scores in both immediate (-0.31 points, 95% CI: -0.57, -0.05) and delayed (-0.37 points, 95% CI: -0.64, -0.10) recall comparing to non-ɛ4 allele carriers. We did not detect any significant longitudinal effect of the ɛ4 allele. There was no cross-sectional or longitudinal effect of the ɛ2 allele. CONCLUSION: The APOEɛ4 allele was identified as a risk factor for poorer episodic memory in older adults, while the APOEɛ2 allele was not significantly associated with any of the cognitive test scores.

Patterns of multi-domain cognitive aging in participants of the Long Life Family Study.

Maintaining good cognitive function at older age is important, but our knowledge of patterns and predictors of cognitive aging is still limited. We used Bayesian model-based clustering to group 5064 participants of the Long Life Family Study (ages 49-110 years) into clusters characterized by distinct trajectories of cognitive change in the domains of episodic memory, attention, processing speed, and verbal fluency. For each domain, we identified 4 or 5 large clusters with representative patterns of change ranging from rapid decline to exceptionally slow change. We annotated the clusters by their correlation with genetic and molecular biomarkers, non-genetic risk factors, medical history, and other markers of aging to discover correlates of cognitive changes and neuroprotection. The annotation analysis discovered both predictors of multi-domain cognitive change such as gait speed and predictors of domain-specific cognitive change such as IL6 and NTproBNP that correlate only with change of processing speed or APOE genotypes that correlate only with change of processing speed and logical memory. These patterns also suggest that cognitive decline starts at young age and that maintaining good physical function correlates with slower cognitive decline. To better understand the agreement of cognitive changes across multiple domains, we summarized the results of the cluster analysis into a score of cognitive function change. This score showed that extreme patterns of change affecting multiple cognitive domains simultaneously are rare in this study and that specific signatures of biomarkers of inflammation and metabolic disease predict severity of cognitive changes. The substantial heterogeneity of change patterns within and between cognitive domains and the net of correlations between patterns of cognitive aging and other aging traits emphasizes the importance of measuring a wide range of cognitive functions and the need for studying cognitive aging in concert with other aging traits.

Biomarker signatures of sickle cell disease severity.

Identifying sickle cell disease patients at high risk of complications could lead to personalized treatment and better prognosis but despite many advances prediction of the clinical course of these patients remains elusive. We propose a system-type approach to discover profiles of multiple, common biomarkers that correlate with morbidity and mortality in sickle cell disease. We used cluster analysis to discover 17 signatures of 17 common circulating biomarkers in 2320 participants of the Cooperative Study of Sickle Cell Disease, and evaluated the association of these signatures with risk for stroke, pain, leg ulceration, acute chest syndrome, avascular necrosis, seizure, death, and trend of fetal hemoglobin and hemolysis using longitudinally collected data. The analysis shows that some of the signatures are associated with reduced risk for complications, while others are associated with increased risk for complications. We also show that these signatures repeat in two more contemporary studies of sickle cell disease and correlate with recently discovered biomarkers of pulmonary vascular disease. With replication and further study, these biomarker signatures could become an important and affordable precision medicine tool to aid treatment and management of the disease.

Factor structure of cognition and functional capacity in two studies of schizophrenia and bipolar disorder: Implications for genomic studies.

OBJECTIVE: Impairments in cognition and everyday functioning are common in schizophrenia and bipolar disorder (BPD). In this article, we present factor analyses of cognitive and functional capacity (FC) measures based on 2 studies of schizophrenia (SCZ) and bipolar I disorder (BPI) using similar methods. The overall goal of these analyses was to determine whether performance-based assessments should be examined individually, or aggregated on the basis of the correlational structure of the tests, as well as to evaluate the similarity of factor structures of SCZ and BPI. METHOD: Veterans Affairs Cooperative Studies Program Study #572 (Harvey et al., 2014) evaluated cognitive and FC measures among 5,414 BPI and 3,942 SCZ patients. A 2nd study evaluated similar neuropsychological (NP) and FC measures among 368 BPI and 436 SCZ patients. Principal components analysis, as well as exploratory and CFAs, were used to examine the data. RESULTS: Analyses in both datasets suggested that NP and FC measures were explained by a single underlying factor in BPI and SCZ patients, both when analyzed separately or as in a combined sample. The factor structure in both studies was similar, with or without inclusion of FC measures; homogeneous loadings were observed for that single factor across cognitive and FC domains across the samples. CONCLUSION: The empirically derived factor model suggests that NP performance and FC are best explained as a single latent trait applicable to people with SCZ and BPD. This single measure may enhance the robustness of the analyses relating genomic data to performance-based phenotypes.

Consistency of Recall for Deployment-Related Traumatic Brain Injury.

OBJECTIVE: To examine the temporal consistency of self-reported deployment-related traumatic brain injury (TBI) and its association with posttraumatic stress disorder (PTSD) symptom severity. SETTING: In-person interviews at US Army installations (postdeployment); phone interviews (long-term follow-up). PARTICIPANTS: A total of 378 US Army soldiers and veterans deployed to Iraq; 14.3% (n = 54) reported TBI with loss of consciousness during an index deployment. DESIGN: Participants were evaluated after returning from deployment and again 5 to 9 years later. MAIN MEASURES: Temporal consistency of TBI endorsement based on TBI screening interviews; PTSD Checklist, Civilian Version. RESULTS: The concordance of deployment-related TBI endorsement from the postdeployment to long-term follow-up assessment was moderate (κ = 0.53). Of the 54 participants reporting (predominantly mild) TBI occurring during an index deployment, 32 endorsed TBI inconsistently over time. More severe PTSD symptoms at postdeployment assessment were independently associated with discordant reporting (P = .0004); each 10-point increase in PCL scores increasing odds of discordance by 69% (odds ratio = 1.69; 95% confidence interval, 1.26-2.26). CONCLUSIONS: Deployment-related TBI may not be reported reliably over time, particularly among war-zone veterans with greater PTSD symptoms. Results of screening evaluations for TBI history should be viewed with caution in the context of PTSD symptom history.