Cross-platform proteomics signatures of extreme old age.

In previous work we used a Somalogic platform targeting approximately 5000 proteins to generate a serum protein signature of centenarians that we validated in independent studies that used the same technology. We set here to validate and possibly expand the results by profiling the serum proteome of a subset of individuals included in the original study using liquid chromatography tandem mass spectrometry (LC-MS/MS). Following pre-processing, the LC-MS/MS data provided quantification of 398 proteins, with only 266 proteins shared by both platforms. At 1% FDR statistical significance threshold, the analysis of LC-MS/MS data detected 44 proteins associated with extreme old age, including 23 of the original analysis. To identify proteins for which associations between expression and extreme-old age were conserved across platforms, we performed inter-study conservation testing of the 266 proteins quantified by both platforms using a method that accounts for the correlation between the results. From these tests, a total of 80 proteins reached 5% FDR statistical significance, and 26 of these proteins had concordant pattern of gene expression in whole blood. This signature of 80 proteins points to blood coagulation, IGF signaling, extracellular matrix (ECM) organization, and complement cascade as important pathways whose protein level changes provide evidence for age-related adjustments that distinguish centenarians from younger individuals.

A longevity-specific bank of induced pluripotent stem cells from centenarians and their offspring.

Centenarians provide a unique lens through which to study longevity, healthy aging, and resiliency. Moreover, models of human aging and resilience to disease that allow for the testing of potential interventions are virtually non-existent. We obtained and characterized over 50 centenarian and offspring peripheral blood samples including those connected to functional independence data highlighting resistance to disability and cognitive impairment. Targeted methylation arrays were used in molecular aging clocks to compare and contrast differences between biological and chronological age in these specialized subjects. Isolated peripheral blood mononuclear cells (PBMCs) were then successfully reprogrammed into high-quality induced pluripotent stem cell (iPSC) lines which were functionally characterized for pluripotency, genomic stability, and the ability to undergo directed differentiation. The result of this work is a one-of-a-kind resource for studies of human longevity and resilience that can fuel the discovery and validation of novel therapeutics for aging-related disease.

Systemic inflammation in relation to exceptional memory in the Long Life Family Study (LLFS).

Background and objectives: We previously found a substantial familial aggregation of healthy aging phenotypes, including exceptional memory (EM) in long-lived persons. In the current study, we aim to assess whether long-lived families with EM and without EM (non-EM) differ in systemic inflammation status and trajectory. Methods: The current study included 4333 participants of the multi-center Long Life Family Study (LLFS). LLFS families were classified as EM (556 individuals from 28 families) or non-EM (3777 individuals from 416 families), with 2 or more offspring exhibiting exceptional memory performance (i.e. having baseline composite z-score representing immediate and delayed story memory being 1.5 SD above the mean in the nondemented offspring sample) considered as EM. Blood samples from baseline were used to measure inflammatory biomarkers including total white blood cell (WBC) and its subtypes (neutrophils, lymphocytes, monocytes) count, platelet count, high sensitivity C-reactive protein, and interleukin-6. Generalized linear models were used to examine cross-sectional differences in inflammatory biomarkers at baseline. In a sub-sample of 2227 participants (338 subjects from 24 EM families and 1889 from 328 non-EM families) with repeated measures of immune cell counts, we examined whether the rate of biomarker change differed between EM and non-EM families. All models were adjusted for family size, relatedness, age, sex, education, field center, APOE genotype, and body mass index. Results: LLFS participants from EM families had a marginally higher monocyte count at baseline (b = 0.028, SE = 0.0110, p = 0.010) after adjusting for age, sex, education, and field site, particularly in men (p < 0.0001) but not in women (p = 0.493) (p-interaction = 0.003). Over time, monocyte counts increased (p < 0.0001) in both EM and non-EM families, while lymphocytes and platelet counts decreased over time in the non-EM families (p < 0.0001) but not in the EM families. After adjusting for multiple variables, there was no significant difference in biomarker change over time between the EM and non-EM families. Discussion: Compared with non-EM families, EM families had significantly higher monocyte count at baseline but had similar change over time. Our study suggests that differences in monocyte counts may be a pathway through which EM emerges in some long-lived families, especially among men.

Whole genome-wide sequence analysis of long-lived families (Long-Life Family Study) identifies MTUS2 gene associated with late-onset Alzheimer's disease.

INTRODUCTION: Late-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics. METHODS: We conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aß) levels. RESULTS: We identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aß42/40 ratio compared to lower amyloid. DISCUSSION: MTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology. HIGHLIGHTS: Long-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

The association between frailty and perceived physical and mental fatigability: The Long Life Family Study.

BACKGROUND: Higher levels of frailty, quantified by a frailty index (FI), may be linked to fatigue severity as tasks become more physically and mentally demanding. Fatigue, a component of frailty research, has been ambiguous and inconsistent in its operationalization. Fatigability-the quantification of vulnerability to fatigue in relation to specific intensity and duration of activities-offers a more sensitive and standardized approach, though the association between frailty and fatigability has not been assessed. METHODS: Using cross-sectional data from the Long Life Family Study at Visit 2 (2014-2017; N = 2524; mean age ± standard deviation (SD) 71.4 ± 11.2 years; 55% women; 99% White), we examined associations between an 83-item FI after excluding fatigue items (ratio of number of health problems reported (numerator) out of the total assessed (denominator); higher ratio = greater frailty) and perceived physical and mental fatigability using the Pittsburgh Fatigability Scale (PFS) (range 0-50; higher scores = greater fatigability). RESULTS: Participants had mean ± standard deviation FI (0.08 ± 0.06; observed range: 0.0-0.43), PFS Physical (13.7 ± 9.6; 39.5% more severe, ≥15), and PFS Mental (7.9 ± 8.9; 22.8% more severe, ≥13). The prevalence of more severe physical and mental fatigability was higher across FI quartiles. In mixed effects models accounting for family structure, a clinically meaningful 3%-higher FI was associated with 1.9 points higher PFS Physical score (95% confidence interval (CI) 1.7-2.1) and 1.7 points higher PFS Mental score (95% CI 1.5-1.9) after adjusting for covariates. CONCLUSIONS: Frailty was associated with perceived physical and mental fatigability severity. Understanding this association may support the development of interventions to mitigate the risks associated with greater frailty and perceived fatigability. Including measurements of perceived fatigability, in lieu of fatigue, in frailty indices has the potential to alleviate the inconsistencies and ambiguity surrounding the operationalization of fatigue and provide a more precise and sensitive measurement of frailty.

Signatures of Neuropsychological Test Results in the Long Life Family Study: A Cluster Analysis.

BACKGROUND: Discovering patterns of cognitive domains and characterizing how these patterns associate with other risk factors and biomarkers can improve our understanding of the determinants of cognitive aging. OBJECTIVE: To discover patterns of cognitive domains using neuropsychological test results in Long Life Family Study (LLFS) and characterize how these patterns associate with aging markers. METHODS: 5,086 LLFS participants were administered neuropsychological tests at enrollment. We performed a cluster analysis of six baseline neuropsychological test scores and tested the association between the identified clusters and various clinical variables, biomarkers, and polygenic risk scores using generalized estimating equations and the Chi-square test. We used Cox regression to correlate the clusters with the hazard of various medical events. We investigated whether the cluster information could enhance the prediction of cognitive decline using Bayesian beta regression. RESULTS: We identified 12 clusters with different cognitive signatures that represent profiles of performance across multiple neuropsychological tests. These signatures significantly correlated with 26 variables including polygenic risk scores, physical and pulmonary functions, and blood biomarkers and were associated with the hazard of mortality (p < 0.01), cardiovascular disease (p = 0.03), dementia (p = 0.01), and skin cancer (p = 0.03). CONCLUSION: The identified cognitive signatures capture multiple domains simultaneously and provide a holistic vision of cognitive function, showing that different patterns of cognitive function can coexist in aging individuals. Such patterns can be used for clinical intervention and primary care.

Multi-modal profiling of peripheral blood cells across the human lifespan reveals distinct immune cell signatures of aging and longevity.

BACKGROUND: Age-related changes in immune cell composition and functionality are associated with multimorbidity and mortality. However, many centenarians delay the onset of aging-related disease suggesting the presence of elite immunity that remains highly functional at extreme old age. METHODS: To identify immune-specific patterns of aging and extreme human longevity, we analyzed novel single cell profiles from the peripheral blood mononuclear cells (PBMCs) of a random sample of 7 centenarians (mean age 106) and publicly available single cell RNA-sequencing (scRNA-seq) datasets that included an additional 7 centenarians as well as 52 people at younger ages (20-89 years). FINDINGS: The analysis confirmed known shifts in the ratio of lymphocytes to myeloid cells, and noncytotoxic to cytotoxic cell distributions with aging, but also identified significant shifts from CD4+ T cell to B cell populations in centenarians suggesting a history of exposure to natural and environmental immunogens. We validated several of these findings using flow cytometry analysis of the same samples. Our transcriptional analysis identified cell type signatures specific to exceptional longevity that included genes with age-related changes (e.g., increased expression of STK17A, a gene known to be involved in DNA damage response) as well as genes expressed uniquely in centenarians' PBMCs (e.g., S100A4, part of the S100 protein family studied in age-related disease and connected to longevity and metabolic regulation). INTERPRETATION: Collectively, these data suggest that centenarians harbor unique, highly functional immune systems that have successfully adapted to a history of insults allowing for the achievement of exceptional longevity. FUNDING: TK, SM, PS, GM, SA, TP are supported by NIH-NIAUH2AG064704 and U19AG023122. MM and PS are supported by NIHNIA Pepper center: P30 AG031679-10. This project is supported by the Flow Cytometry Core Facility at BUSM. FCCF is funded by the NIH Instrumentation grant: S10 OD021587.

Mosaic Chromosomal Alterations and Human Longevity.

Mosaic chromosomal alterations (mCAs) are structural alterations associated with aging, cancer, cardiovascular disease, infectious diseases, and mortality. The distribution of mCAs in centenarians and individuals with familial longevity is poorly understood. We used MOsaic CHromosomal Alteration (MoChA) to discover mCAs in 2050 centenarians, offspring, and 248 controls from the New England Centenarian Study (NECS) and in 3 642 subjects with familial longevity and 920 spousal controls from the Long-Life Family Study (LLFS). We analyzed study-specific associations of somatic mCAs with age, familial longevity, the incidence of age-related diseases, and mortality and aggregated the results by meta-analysis. We show that the accumulation of mCAs > 100 KB increased to 102 years and plateaued at older ages. Centenarians and offspring accumulated fewer autosomal mCAs compared with controls (relative risk 0.637, p = .0147). Subjects with the APOE E4 allele had a 35.3% higher risk of accumulating autosomal mCAs (p = .002). Males were at higher risk for mCAs compared to females (male relative risk 1.36, p = 5.15e-05). mCAs were associated with increased hazard for cancer (hazard ratio 1.2) and dementia (hazard ratio 1.259) at a 10% false discovery rate. We observed a borderline significant association between mCAs and risk for mortality (hazard ratio 1.07, p = .0605). Our results show that the prevalence of individuals with mCAs does not continue to increase at ages >102 years and factors promoting familial longevity appear to confer protections from mCAs. These results suggest that limited mCA accumulation could be an important mechanism for extreme human longevity that needs to be investigated.

Rare genetic variants correlate with better processing speed.

We conducted a genome-wide association study of Digit Symbol Substitution Test scores administered in 4207 family members of the Long Life Family Study (LLFS). Genotype data were imputed to the HRC panel of 64,940 haplotypes resulting in ∼15M genetic variants with a quality score > 0.7. The results were replicated using genetic data imputed to the 1000 Genomes phase 3 reference panel from 2 Danish twin cohorts: the study of Middle Aged Danish Twins and the Longitudinal Study of Aging Danish Twins. The genome-wide association study in LLFS discovered 18 rare genetic variants (minor allele frequency (MAF) < 1.0%) that reached genome-wide significance (p-value < 5 × 10-8). Among these, 17 rare variants in chromosome 3 had large protective effects on the processing speed, including rs7623455, rs9821776, rs9821587, rs78704059, which were replicated in the combined Danish twin cohort. These SNPs are located in/near 2 genes, THRB and RARB, that belonged to the thyroid hormone receptors family that may influence the speed of metabolism and cognitive aging. The gene-level tests in LLFS confirmed that these 2 genes are associated with processing speed.

A metabolomic signature of the APOE2 allele.

With the goal of identifying metabolites that significantly correlate with the protective e2 allele of the apolipoprotein E (APOE) gene, we established a consortium of five studies of healthy aging and extreme human longevity with 3545 participants. This consortium includes the New England Centenarian Study, the Baltimore Longitudinal Study of Aging, the Arivale study, the Longevity Genes Project/LonGenity studies, and the Long Life Family Study. We analyzed the association between APOE genotype groups E2 (e2e2 and e2e3 genotypes, N = 544), E3 (e3e3 genotypes, N = 2299), and E4 (e3e4 and e4e4 genotypes, N = 702) with metabolite profiles in the five studies and used fixed effect meta-analysis to aggregate the results. Our meta-analysis identified a signature of 19 metabolites that are significantly associated with the E2 genotype group at FDR < 10%. The group includes 10 glycerolipids and 4 glycerophospholipids that were all higher in E2 carriers compared to E3, with fold change ranging from 1.08 to 1.25. The organic acid 6-hydroxyindole sulfate, previously linked to changes in gut microbiome that were reflective of healthy aging and longevity, was also higher in E2 carriers compared to E3 carriers. Three sterol lipids and one sphingolipid species were significantly lower in carriers of the E2 genotype group. For some of these metabolites, the effect of the E2 genotype opposed the age effect. No metabolites reached a statistically significant association with the E4 group. This work confirms and expands previous results connecting the APOE gene to lipid regulation and suggests new links between the e2 allele, lipid metabolism, aging, and the gut-brain axis.

Association between late maternal age and age-related endophenotypes in the Long Life Family Study.

Extended maternal age has been suggested as marker of delayed age-associated disabilities. We use the Long Life Family Study (LLFS) offspring generation to investigate the association between extended maternal age at last childbirth and healthy-aging endophenotypes. We hypothesize that women with extended maternal age at last childbirth will exhibit healthier endophenotype profiles compared to younger mothers. The association between maternal age and age-related endophenotypes previously derived in LLFS was assessed using Generalized Estimating Equations to adjust for relatedness. The quartiles of the maternal age at last childbirth were modeled as the independent variables. Univariate analyses tested the association between maternal age at last childbirth and age at clinical assessment, education, field center, Apolipoprotein E (APOE) genotype, depression, stress, smoking and successful pregnancies. Only the variables significantly associated in the univariate analyses were considered in secondary multivariate analyses. Univariate analyses showed that compared to older mothers (age at last birth ≥35), mothers 30 years old or younger at last childbirth are less educated (12 ± 3 years versus 13 ± 3 years) and have a higher frequency of smoking (9% versus 3% for maternal age ≥35). Results showed that older mothers (age at last birth ≥31-34 or ≥ 35) demonstrated significantly better cognitive profiles (p = 0.017 and p = 0.021 respectively) compared with mothers with last childbirth age ≤30. Later maternal age among women from long-life families is associated with a better cognitive profile, supporting the hypothesis that later age at childbirth may be a marker for healthy aging.

The Boston Process Approach and Digital Neuropsychological Assessment: Past Research and Future Directions.

Neuropsychological assessment using the Boston Process Approach (BPA) suggests that an analysis of the strategy or the process by which tasks and neuropsychological tests are completed, and the errors made during test completion convey much information regarding underlying brain and cognition and are as important as overall summary scores. Research over the last several decades employing an analysis of process and errors has been able to dissociate between dementia patients diagnosed with Alzheimer's disease, vascular dementia associated with MRI-determined white matter alterations, and Parkinson's disease; and between mild cognitive impairment subtypes. Nonetheless, BPA methods can be labor intensive to deploy. However, the recent availability of digital platforms for neuropsychological test administration and scoring now enables reliable, rapid, and objective data collection. Further, digital technology can quantify highly nuanced data previously unobtainable to define neurocognitive constructs with high accuracy. In this paper, a brief review of the BPA is provided. Studies that demonstrate how digital technology translates BPA into specific neurocognitive constructs using the Clock Drawing Test, Backward Digit Span Test, and a Digital Pointing Span Test are described. Implications for using data driven artificial intelligence-supported analytic approaches enabling the creation of more sensitive and specific detection/diagnostic algorithms for putative neurodegenerative illness are also discussed.

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.

Distribution of 54 polygenic risk scores for common diseases in long lived individuals and their offspring.

A surprising and well-replicated result in genetic studies of human longevity is that centenarians appear to carry disease-associated variants in numbers similar to the general population. With the proliferation of large genome-wide association studies (GWAS) in recent years, investigators have turned to polygenic scores to leverage GWAS results into a measure of genetic risk that can better predict the risk of disease than individual significant variants alone. We selected 54 polygenic risk scores (PRSs) developed for a variety of outcomes, and we calculated their values in individuals from the New England Centenarian Study (NECS, N = 4886) and the Long Life Family Study (LLFS, N = 4577). We compared the distribution of these PRSs among exceptionally long-lived individuals (ELLI), their offspring, and controls, and we also examined their predictive values, using t-tests and regression models adjusting for sex and principal components reflecting the ancestral background of the individuals (PCs). In our analyses, we controlled for multiple testing using a Bonferroni-adjusted threshold for 54 traits. We found that only 4 of the 54 PRSs differed between ELLIs and controls in both cohorts. ELLIs had significantly lower mean PRSs for Alzheimer's disease (AD) and coronary artery disease (CAD) than controls, suggesting a genetic predisposition to extreme longevity may be mediated by reduced susceptibility to these traits. ELLIs also had significantly higher mean PRSs for improved cognitive function and parental extreme longevity. In addition, the PRS for AD was associated with a higher risk of dementia among controls but not ELLIs (p = 0.003, 0.3 in NECS, p = 0.03, 0.9 in LLFS, respectively). ELLIs have a similar burden of genetic disease risk as the general population for most traits but have a significantly lower genetic risk of AD and CAD. The lack of association between AD PRS and dementia among ELLIs suggests that the genetic risk for AD that they do have is somehow counteracted by protective genetic or environmental factors.

A Genome-Wide Association Study of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants.

We performed a genome-wide association study (GWAS) of human extreme longevity (EL), defined as surviving past the 99th survival percentile, by aggregating data from four centenarian studies. The combined data included 2304 EL cases and 5879 controls. The analysis identified a locus in CDKN2B-AS1 (rs6475609, p = 7.13 × 10-8) that almost reached genome-wide significance and four additional loci that were suggestively significant. Among these, a novel rare variant (rs145265196) on chromosome 11 had much higher longevity allele frequencies in cases of Ashkenazi Jewish and Southern Italian ancestry compared to cases of other European ancestries. We also correlated EL-associated SNPs with serum proteins to link our findings to potential biological mechanisms that may be related to EL and are under genetic regulation. The findings from the proteomic analyses suggested that longevity-promoting alleles of significant genetic variants either provided EL cases with more youthful molecular profiles compared to controls or provided some form of protection from other illnesses, such as Alzheimer's disease, and disease progressions.

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.

Survey Findings About the Experiences, Challenges, and Practical Advice/Solutions Regarding Teleneuropsychological Assessment in Adults.

OBJECTIVE: In the wake of the coronavirus pandemic, teleneuropsychology utilization has increased. There is a need to characterize the first-hand experiences of individuals using teleneuropsychology, identify the common teleneuropsychology challenges, and devise practical strategies for mitigating/resolving these challenges. METHOD: Survey data were collected from U.S. based neuropsychologists and other individuals (e.g., graduate students and research assistants) who were engaged in remote cognitive assessment with adults (n = 87). Frequency analyses were conducted to examine: how respondents used teleneuropsychology (e.g., duration of use, types of measures and devices/technology platforms used); challenges that were encountered with different technology platforms and teleneuropsychology use; and advice for navigating these challenges. RESULTS: Most respondents began using teleneuropsychology relatively recently in the context of the coronavirus pandemic, with home-to-home or clinic-to-home settings being the most frequently reported teleneuropsychology settings. Zoom®, Doxy.Me®, and MyChart® were the most frequently used platforms, largely due to workplace mandates and/or Health Insurance Portability and Accountability Act-compliant features. Common challenges with teleneuropsychology included internet connection issues and environmental distractions in examinees' homes, and examinees having limited-to-no access to technologies requisite for teleneuropsychology. Providing clear instructions to the examinee prior to the teleneuropsychology visit was the most common advice for ensuring a successful teleneuropsychology evaluation. Similar response patterns were generally noted for those who used TeleNP for clinical or research purposes. CONCLUSIONS: These survey results reflect common experiences and challenges with teleneuropsychology and identify priority targets for increasing its feasibility, reliability, and validity. Findings provide context for the development of formal teleneuropsychology competencies.

Perceived Physical Fatigability Predicts All-Cause Mortality in Older Adults.

BACKGROUND: Perceived physical fatigability is highly prevalent in older adults and associated with mobility decline and other health consequences. We examined the prognostic value of perceived physical fatigability as an independent predictor of risk of death among older adults. METHODS: Participants (N = 2 906), mean age 73.5 [SD, 10.4] years, 54.2% women, 99.7% white enrolled in the Long Life Family Study, were assessed at Visit 2 (2014-2017) with 2.7 [SD, 1.0] years follow-up. The Pittsburgh Fatigability Scale (PFS), a 10-item, self-administered validated questionnaire (score range 0-50, higher = greater fatigability) measured perceived physical fatigability at Visit 2. Deaths post-Visit 2 through December 31, 2019 were identified by family members notifying field centers, reporting during another family member's annual phone follow-up, an obituary, or Civil Registration System (Denmark). We censored all other participants at their last contact. Cox proportional hazard models predicted mortality by fatigability severity, adjusted for family relatedness and other covariates. RESULTS: Age-adjusted PFS Physical scores were higher for those who died (19.1 [SE, 0.8]) compared with alive (12.2, [SE, 0.4]) overall, as well as across age strata (p < .001), except for those 60-69 years (p = .79). Participants with the most severe fatigability (PFS Physical scores ≥ 25) were over twice as likely to die (hazard ratio, 2.33 [95% CI, 1.65-3.28]) compared with those who had less severe fatigability (PFS Physical scores < 25) after adjustment. CONCLUSIONS: Our work underscores the utility of the PFS as a novel patient-reported prognostic indicator of phenotypic aging that captures both overt and underlying disease burden that predicts death.

APOE E2/E2 Is Associated with Slower Rate of Cognitive Decline with Age.

BACKGROUND: The E4 allele of the APOE gene is known to be associated with cognitive impairment. However, a limited number of studies have examined the association between the E2 allele and longitudinal changes of cognitive function. OBJECTIVE: To determine whether rates of cognitive change differ in carriers of the APOE E2 allele compared to other genotypes. METHODS: We conducted a secondary analysis of data from two ongoing longitudinal cohort studies, the Long Life Family Study (LLFS) and New England Centenarian Study (NECS). We included participants who had APOE genotyping data, data from longitudinal administrations of the Telephone Interview for Cognitive Status (TICS), and age, sex, and education available. We assessed whether cognitive change as measured by rate of decline in TICS score differed among people with different APOE genotypes. We used a hierarchical mixed effect model with APOE genotypes, their interactions with age, and potential confounders. RESULTS: After adjusting for sex and education, in carriers of the common E3/E3 genotype, TICS score decreased by 0.15 points per year of age. In those with the E2/E2 genotype, TICS score decreased by 0.05 points per year of age, a significantly slower rate of decline (p = 0.017). We observed no protective effect of the E2/E3 genotype on cognitive decline. CONCLUSION: These results suggest a protective effect of the E2/E2 genotype on a measure of global cognitive function.

Digital Technology Differentiates Graphomotor and Information Processing Speed Patterns of Behavior.

BACKGROUND: Coupling digital technology with traditional neuropsychological test performance allows collection of high-precision metrics that can clarify and/or define underlying constructs related to brain and cognition. OBJECTIVE: To identify graphomotor and information processing trajectories using a digitally administered version of the Digit Symbol Substitution Test (DSST). METHODS: A subset of Long Life Family Study participants (n = 1,594) completed the DSST. Total time to draw each symbol was divided into 'writing' and non-writing or 'thinking' time. Bayesian clustering grouped participants by change in median time over intervals of eight consecutively drawn symbols across the 90 s test. Clusters were characterized based on sociodemographic characteristics, health and physical function data, APOE genotype, and neuropsychological test scores. RESULTS: Clustering revealed four 'thinking' time trajectories, with two clusters showing significant changes within the test. Participants in these clusters obtained lower episodic memory scores but were similar in other health and functional characteristics. Clustering of 'writing' time also revealed four performance trajectories where one cluster of participants showed progressively slower writing time. These participants had weaker grip strength, slower gait speed, and greater perceived physical fatigability, but no differences in cognitive test scores. CONCLUSION: Digital data identified previously unrecognized patterns of 'writing' and 'thinking' time that cannot be detected without digital technology. These patterns of performance were differentially associated with measures of cognitive and physical function and may constitute specific neurocognitive biomarkers signaling the presence of subtle to mild dysfunction. Such information could inform the selection and timing of in-depth neuropsychological assessments and help target interventions.