Abstract Background Hemoglobin A1c (HbA1c), an important diagnostic biomarker for type 2 diabetes (T2D), is also associated with aging, cognitive performance, and mortality. To identify epistatic interactions, we assessed 133 known gene variants associated with HbA1c among 3,778 non-diabetic subjects of European ancestry in the Long Life Family Study (LLFS). Methods We applied Bayesian Imputation Based Association Mapping (BIMBAM) to identify significant pairwise epistatic interactions among genetic variants that were previously shown to be associated with levels of HbA1c. To take into account confounding effects, we adjusted age, sex, field centers, body mass index (BMI), and genetic principal components (PCs). Results This analysis yielded seven pairs with log10(BF)>10; of those, six pairs were confirmed using a full-term mixed regression model. Specifically, these included significant interactions of HK1-rs17476364 with variants in GCK (rs2971670, rs4607517) or G6PC2 (rs560887), as well as between HK1-rs16926246 and the same variants (P values for each term ≤ 7.14e-3). All epistatic interactions between HK1 and GCK, and between HK1 and G6PC2 were replicated in two large independent studies (namely, Framingham Offspring Study, P < 0.05; Health and Retirement Study, P < 0.05). Conclusion The present study revealed that HK1 and GCK interact to contribute to regulating levels of HbA1c and are likely to be involved in molecular mechanisms underlying healthy aging processes. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number U19AG063893. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: IRB at Washington University in St. Louis gave ethical approval for this work. IRB ID #201904204=1025. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes LLFS clinical data and WGS data can be downloaded at ELITE Synapse portal ( syn52663596). FOS data is available at dbGAP with accession phs000007.v35.p16 and phg002135, and HRS data can be downloaded at https://hrs.isr.umich.edu with accession phs000428.v2.p2.

There are various well-validated taxonomic classifiers for profiling shotgun metagenomics data, with two popular methods, MetaPhlAn (marker-gene-based) and Kraken (k-mer-based), at the forefront of many studies. Despite differences between classification approaches and calls for the development of consensus methods, most analyses of shotgun metagenomics data for microbiome studies use a single taxonomic classifier. In this study, we compare inferences from two broadly used classifiers, MetaPhlAn4 and Kraken2, applied to stool metagenomic samples from participants in the Integrative Longevity Omics study to measure associations of taxonomic diversity and relative abundance with age, replicating analyses in an independent cohort. We also introduce consensus and meta-analytic approaches to compare and integrate results from multiple classifiers. While many results are consistent across the two classifiers, we find classifier-specific inferences that would be lost when using one classifier alone. Both classifiers captured similar age-associated changes in diversity across cohorts, with variability in species alpha diversity driven by differences by classifier. When using a correlated meta-analysis approach (AdjMaxP) across classifiers, differential abundance analysis captures more age-associated taxa, including 17 taxa robustly age-associated across cohorts. This study emphasizes the value of employing multiple classifiers and recommends novel approaches that facilitate the integration of results from multiple methodologies.

Although aging is a universal event, some individuals are able to achieve extreme longevity. The Long-Life Family Study (LLFS) enrolls participants from families enriched with long-lived individuals, serves as a valuable dataset for studying ageing phenotypes and identify potential intervention targets. We analyzed the association between age at blood draw and 16,284 RNAseq-based blood transcriptomic data from 2,167 LLFS participants with ages ranging from 18 to 107, replicated the results in the Integrative Longevity Omics Study (ILO) dataset of 20,884 RNAseq-based blood transcriptomic data from 419 participants, with ages ranging from 60 to 108, and further compared our findings to a published reference aging signature. We identified 4,227 transcripts increasing and 4,044 transcripts decreasing with age, and enrichment analysis revealed age-related upregulation of inflammatory and senescence-related pathways, and downregulation of MYC and Wnt/β-catenin targets, among others. Further, a subset of transcripts showed age associations unique to the longevity-enriched cohorts (LLFS and ILO). We also identified 314 transcripts significantly associated with mortality risk and found that pro-survival gene sets included NK cell-mediated cytotoxicity and GPCR signaling. Finally, increased transcriptomic age predicted using transcriptomic clock was strongly associated with increased mortality. In summary, this study identified robust transcriptomic signatures of aging and mortality in a longevity-enriched population, highlighting key biological pathways such as immune modulation, inflammation, and senescence.

Background Many centenarian offspring (CO) show survival and health advantages compared to population controls, yet little is known about their dietary patterns. The New England Centenarian Study (NECS) offers an opportunity to characterize diet quality in this unique longevity-enriched population. Objective To characterize overall and component-level diet quality among CO in the New England Centenarian Study (NECS) using four established indices and to contextualize these patterns relative to published benchmarks from large U.S. cohorts of older adults. Design We analyzed data from 457 NECS participants who completed a 131-item food frequency questionnaire in 2005. We computed dietary scores using the Alternative Healthy Eating Index (AHEI), Healthy Eating Index (HEI), Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet, and Planetary Health Diet Index (PHDI). We performed linear regression to examine whether these scores differ by sex, age, education, and marital status. Results Participants’ mean (SD) age was 73.6 (9.2) years; 55.1% were women. Overall mean (SD) index scores were: AHEI 51.9 (11.0), HEI 70.1 (9.2), MIND 8.6 (1.9), and PHDI 87.1 (12.0), indicating moderate overall diet quality. NECS participants generally met or approached targets for intakes of fruits, greens/beans, and protein-food quality (including seafood), as well as for moderation components such as sodium, added sugar, and refined grains. However, they fell short on intakes of legumes/soy/nuts and whole grains. Compared with nationally representative studies, NECS participants had modestly higher overall dietary scores across the four indices (P < 0.001). NECS participants had higher component scores for intakes of fruits, vegetables, and omega-3 s, but lower scores for whole grains, legumes, and soy. Higher education was consistently associated with healthier diet scores, while younger age and female sex corresponded to more favorable component patterns. Conclusion Centenarian offspring exhibit moderately higher diet quality than average U.S. older adults, with clear strengths and persistent gaps. These findings provide the first reference profile of dietary patterns in a longevity-enriched population and establish a foundation for future longitudinal research on the interaction of nutrition with inherited resilience to support healthy aging.

Centenarian offspring (CO) in the New England Centenarian Study (NECS) typically show survival and health advantages, yet little is known about their dietary intake patterns. In this study, we characterized participants’ diets according to four established patterns: Alternative Healthy Eating Index (AHEI), Healthy Eating Index (HEI), Mediterranean-DASH (Dietary Approaches to Stop Hypertension) Intervention for Neurodegenerative Delay (MIND), and Planetary Health Diet Index (PHDI) in CO and a referent group and compared them to national dietary surveys. NECS participants (335 CO; 128 controls; mean age: 73.6 years; 55.1% women) completed the Harvard 131-item food frequency questionnaire in 2005. We assessed each index according to published scoring systems and performed linear regression to examine differences by CO status, sex, age, and education, and compared mean scores to nationally representative data (e.g., National Health and Nutrition Examination Survey [NHANES ]) for older individuals. We found no significant differences between CO and referents across all four indices. However, women had slightly higher AHEI and HEI scores than men (P < 0.05). Younger participants scored higher on AHEI, while education was positively associated with all indices (P < 0.01). Compared to NHANES participants of similar ages, NECS participants scored modestly higher on all indices; however, intakes of whole grains and dairy were below national averages, while seafood protein and added sugar were higher. In summary, CO showed no advantage in dietary quality compared to controls, whereas sociodemographic factors were significant predictors of eating patterns. Future research should explore the diet-physiology-lifestyle interaction and its combined effect on CO’s survival advantage.

Aging is a heterogeneous process that unfolds differently across individuals and biological systems. While single biological clocks provide valuable insights, they often fail to capture the complex and multidimensional nature of aging. In this study, we developed system-specific aging clocks using metabolomics data from the Integrative Longevity Omics study to better understand the heterogeneity of aging trajectories. Each clock was designed to estimate biological age within a distinct metabolic system, under the assumption that variability in system-specific function reflects unique aspects of the aging process. Our analyses revealed striking inter-individual variability: some participants consistently exhibited age acceleration across systems, others showed age deceleration, and many demonstrated mixed patterns depending on the system measured. To further explore this heterogeneity, we clustered participants into subgroups based on their system-specific aging profiles. We then examined associations between these subgroups and (1) the Nutrient Variety Index (NVI), a comprehensive metric summarizing dietary diversity across 19 nutrient groups, (2) cognitive performance, and (3) mortality risk. We found that several subgroups displayed significant associations with multiple NVIs, particularly those reflecting balanced intake of carbohydrates. These same subgroups also showed more favorable cognitive outcomes and reduced mortality risk, suggesting that consistent patterns of healthy aging may be linked to dietary diversity and nutritional balance. Conversely, other subgroups displayed discordant patterns of aging acceleration and were associated with poorer outcomes. These findings highlight that aging is not uniform but system-specific, and that metabolomic aging clocks offer a promising framework for uncovering distinct pathways shaping healthy aging.

Despite calls for the development of consensus methods, most analyses of shotgun metagenomics data for microbiome studies use a single taxonomic classifier. In this study, we compare inferences from two broadly used classifiers, MetaPhlAn4 (marker-gene-based) and Kraken2 (k-mer-based), applied to stool metagenomic samples from participants in the Integrative Longevity Omics study to measure associations of taxonomic diversity and relative abundance with age, replicating analyses in an independent cohort. We also introduce consensus and meta-analytic approaches to compare and integrate results from multiple classifiers. While many results are consistent across the two classifiers, we find classifier-specific inferences that would be lost when using one classifier alone. When using a correlated meta-analysis approach across classifiers, differential abundance analysis captures more age-associated taxa, including 17 taxa robustly age-associated across cohorts. This study emphasizes the value of employing multiple classifiers and recommends novel approaches that facilitate the integration of results from multiple methodologies. ### Competing Interest Statement The authors have declared no competing interest. National Institute on Aging, https://ror.org/049v75w11, UH2/UH3AG064704 National Institutes of Health, https://ror.org/01cwqze88, S10OD032203

As the need to assess cognitive function in older adults increases, it is crucial to understand how hearing may impact cognitive test performance since many tasks are administered orally. While audiometry remains the gold standard for measuring hearing loss, other methods such as self-reports are easier to collect during remote assessments and/or in large cohort studies. Centenarian (n = 291, mean age 102.2 ± 2.2 years) and offspring (n = 481, mean age 74.0 ± 7.6 years) participants from the Integrative Longevity Omics study and Longevity Consortium Centenarian Project filled out self-rated hearing ability (Likert scale from ‘excellent’ to ‘unable to hear’) and the Hearing Handicap Inventory (HHIE, range 0-40, cutoff > =10). Examiners administered a cognitive screener (i.e, Mini-Mental State Examination [MMSE]) and indicated whether hearing impairment affected the test. In stratified analyses by generation, we used linear regressions with each measure of hearing impairment adjusting for age, sex, and education to predict MMSE score. The prevalence of hearing impairment ranged from 55% to 73% among centenarians depending on the assessment modality and from 2% to 33% for offspring. Only 10.2% of centenarians and 0% of offspring were rated as hearing impaired across all three measures. Examiner-rated validity was a significant predictor of MMSE performance (p < 0.001) in both generations, while self-rated hearing was a significant predictor only among centenarians (p < 0.01). These scales capture different aspects and levels of hearing impairment and thus both research and clinical settings should consider using multiple scales to account for the impact of hearing ability on cognitive test performance.

Introduction:Polygenic risk scores (PRS) have been used to assess an individual's risk for various diseases, including Alzheimer's disease (AD). This study applied the PRS approach to a cohort of families ascertained for healthy aging, that have shown a reduced risk of AD. Using the SNPs identified as significantly associated with AD in the study by Kunkle and colleagues, we examined the utility of PRS for predicting AD risk in a cohort ascertained for familial healthy aging. Methods:We restricted the study to US LLFS study participants who have been evaluated for AD and have available whole genome sequencing (WGS) data. AD diagnosis was based on consensus diagnosis, and for those without consensus diagnosis, we used the algorithm based on standardized memory scores. PRS were calculated using a published weighted formula. To further examine the predictability of PRS, we assessed the relationship between PRS and AD biomarkers, including Aβ42, Aβ40, NfL, and GFAP. Mixed effects models were used to adjust for confounders as well as relatedness among family members. Given the age at onset of common late onset AD, the present study included those who were at least 65 years of age. Results:We observed that PRS had limited predictive power for AD in this healthy aging cohort. Yet, allele frequencies for the SNPs used in PRS estimation differed between the two studies in a small number (9.7%) of SNPs, suggesting that the lack of effect of the PRS is likely to be due to the small number of AD associated SNPs (12.3% and 16.1%). Subsequent analysis observed no significant association between PRS and biomarkers. This was explained by the low number of SNPs significantly associated with each of the biomarkers. Conclusions:This study highlights the importance of ascertainment of study population in interpreting PRS. In LLFS, a population at reduced risk of AD, PRS based on genetic variants identified from the general population may be inadequate to explain the variability in AD risk. Our results suggest that genetic risk variants, the basis of PRS, may need to be adjusted according to the study population of interest.

We previously identified a signature of 16 serum proteins that highlighted a role of the e2 allele of APOE in lipid regulation via apolipoprotein B (APOB) and apolipoprotein E (APOE), and in inflammation. The serum proteins were profiled using the aptamer-based Somalogic technology. Here, we validate and expand the serum protein signature of APOE using a combination of mass-spectrometry, ELISA, Luminex, antibody-based Olink proteomics, and blood transcriptomics. We replicate the association between APOB and the e2 allele of APOE, we correct the pattern of association between APOE genotypes and serum level of APOE, and we detect new associations between APOE genotypes and the complex of apolipoproteins APOC1, APOC4, APOC2, APOC3, APOE, APOF and APOL1. In addition, we discover 13 new proteins that correlate with APOE genotypes. This extended signature includes granule proteins CAMP, CTSG, DEFA3, and MPO secreted from neutrophils and points to olfactomedin 4 (OLFM4) as a new target for the prevention of Alzheimer's disease.

BACKGROUND:The SuperAgers Family study aims to investigate phenotypic and genetic mechanisms related to healthy aging in nonagenarians, centenarians, and their family members. A remote study design was tested to demonstrate the feasibility of using digital technology to conduct health research within this rare population of advanced age. This paper describes key design elements of the digital research platform developed to deliver consent, enrollment, and study data collection in a cohort of older adults. METHODS:SuperAgers participants aged 95 years or older, their offspring, and offspring's spouses were invited to join the study via media and community outreach. Participants completed registration, consent, submitted study data, and completed remote biospecimen collection via the web-based study app. Platform design elements and functionality were adapted for use by older-aged adults. Qualitative process evaluation assessed usability and participant data entry completion throughout the study workflow. RESULTS:Preliminary data from SuperAgers (n = 160) of average age 98 years (±3 standard deviation [SD]) and offspring/spouses (n = 127) of average age 69 years (±5 SD) were evaluated. About 97% of participants in both groups successfully used the platform to complete eligibility screening, eConsent, and study surveys. CONCLUSIONS:SuperAgers and offspring successfully used the digital research platform to complete eConsent and submit study data. This supports the feasibility of conducting digitally enabled research in older-aged populations using tailored platform design elements that increase usability and minimize entry errors. These findings may contribute to the development of best practices for digitally delivered research studies in aging populations.

Background:Recent studies have revealed a strong association between the e2 allele of the Apolipoprotein E (APOE2) gene and lipid metabolites. In addition, APOE2 carriers appear to be protected from cognitive decline and Alzheimer's disease. This correlation supports the hypothesis that lipids may mediate the protective effect of APOE2 on cognitive function, thereby providing potential targets for therapeutic intervention. Methods:We conducted a causal mediation analysis to estimate both the direct effect of APOE2 and its indirect effect through 19 lipid species on cognitive function, using metrics from the digital Clock Drawing Test (CDT) in 1291 Long Life Family Study (LLFS) participants. The CDT metrics included think-time, ink-time, and their sum as total-time to complete the test. Results:Compared to carriers of the common APOE3, APOE2 carriers completed the CDT significantly faster. Two lipids showed protective mediation when elevated in the blood, resulting in shorter CDT think-time (CE 18:3), ink-time (TG 56:5), and total completion time (CE 18:3 and TG 56:5). Elevated TG 56:4, in contrast, showed deleterious mediation resulting in increased ink-time. The combined indirect effect through all lipids significantly mediated 23.1% of the total effect of APOE2 on total-time, reducing it by 0.92s (95% CI: 0.17, 2.00). Additionally, the sum of total indirect effect from all lipids also mediated 27.3% of the total effect on think-time, reducing it by 0.75s, and 13.6% of the total effect on ink-time, reducing it by 0.17s, though these reductions were statistically insignificant. Sensitivity analysis yielded consistent results of the combined indirect effects and total effects and identified additional significant lipid pathways (CE 22:6, TG 51:3, and TG 54:2). Conclusions:We found that the combined indirect effect through all lipids could mediate 10%-27% of the total direct effect of APOE2 on CDT times. We identified both protective and deleterious lipids, providing insights for new therapeutics targeting those lipids to modulate the protective effects of APOE2 on cognition.

Frailty and functional limitations decrease quality of life for older adults and are associated with myriad health risks. The gut microbiome is a potential therapeutic avenue for promoting functioning among older adults, but a clearer understanding of mechanisms by which commensal gut bacteria may affect frailty and functional independence is needed. In this study, we analyzed data from an ongoing cohort study, Integrative Longevity Omics (ILO), which has 418 shotgun metagenomics samples of the gut microbiome from centenarians and their offspring. We measured associations of microbial alpha/beta diversity and species with function measures (activities of daily living [ADLs] and instrumental activities of daily living [IADLs]) and Fried frailty phenotype domains (physical activity, fatigability, grip strength, weight loss). Species-level alpha diversity decreased with increasing Pittsburgh fatigability score(β=-0.0051, 95% CI:-0.0098 to -0.0003, p = 0.038), adjusting for age, sex, and education. Beta diversity (Bray-Curtis dissimilarity) was associated with ADLs(R2=0.005, p = 0.002), IADLs(R2=0.005, p = 0.006), and fatigability(R2=0.010, p ≤ 0.001), adjusting for age, sex, and education using PERMANOVA. Finally, we identified several species associated with multiple frailty and functioning scores, including Anareostipes hadrus, which was associated with improved ADLs, IADLs, fatigability, and lower likelihood of substantial weight loss, and is a known anti-inflammatory butyrate producer. Worse ADLs/IADLs and greater fatigability was associated with Clostridium innocuum, a commensal gut bacteria with documented potential for virulence. These results identify microbial species for further analysis in association with other ‘omics layers and for future functional studies to understand their potential mechanistic effects on frailty and functioning outcomes in older adults.

OBJECTIVE:Familial longevity, educational attainment, and engagement in cognitively stimulating activities are independently protective for cognitive aging, yet little is known about how these factors relate with one another. We explored the interplay between familial longevity, life exposures that confer cognitive resilience, and cognitive function in the Long Life Family Study. METHOD:A series of Bayesian hierarchical regression models was used to examine the associations among familial longevity, educational attainment, participation in cognitively stimulating activities, and neuropsychological test performance in several cognitive domains in an ancillary observational study of Long Life Family Study family members and a referent cohort (N = 314, M = 75.7, SD = 14.6 years). Models were adjusted by age, sex, and upstream variables along the regression pathway (i.e., cognitive activity, education, and familial longevity), and incorporated a random intercept for family relatedness. RESULTS:Referents had greater engagement in cognitive activities, and in turn, those with higher levels of education and cognitive activity exhibited better neuropsychological performance. Greater cognitive activity was specifically associated with better executive functioning, episodic memory, and language scores. Although Long Life Family Study family members engaged in cognitive activities less often than referents, they performed better on tests of episodic memory, and matched performance on tests of executive function, language, and visuoconstruction. CONCLUSIONS:These results suggest that familial longevity and engagement in cognitively stimulating activities represent two distinct pathways that contribute to preserved cognition in older adulthood, though these findings should be replicated in more diverse samples. Furthermore, these unique pathways differ across tests and cognitive domains. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Extensive research has examined the direct effect of APOE alleles on cognitive decline. However, there is limited investigation into the effect of APOE that is explained or mediated through molecular pathways, such as lipids. In this study, we performed a causal mediation analysis to estimate both the direct effect of APOE2 and its indirect effect through 24 lipid species on cognitive function, measured from the digital Clock Drawing Test (CDT) in 1228 Long Life Family Study (LLFS) participants. Results showed that APOE2 carriers completed the CDT significantly faster compared to common APOE3 carriers. Primary analysis identified two lipids (CE 18:3 and TG 56:5) protectively mediated the effect of APOE2 on cognitive function, resulting in shorter CDT think-time, ink-time, and total-time; conversely, TG 56:4 deleteriously mediated the effect of APOE2, resulting in increased ink-time. Secondary analysis yielded consistent results and identified four additional significant lipid pathways (DG 38:5, TG 51:3, TG 56:1, TG 56:2) that mediated the effect of APOE2. The combined indirect effect in the primary analysis contributed 15%-30% mediated proportion on CDT times, though such mediated proportion did not reach statistical significance. Overall, our analysis identified seven lipid species that significantly mediate the effect of APOE2 on cognitive performance. These lipids represent distinct lipid pathways, including both protective and deleterious mediation effects. Our findings offer insights for new therapeutics targeting those lipids to enhance the protective effects of APOE2 on cognition.

Using whole-genome sequencing (WGS) might offer insights into rare genetic variants associated with healthy aging and extreme longevity (EL), potentially pointing to useful therapeutic targets. In this study, we conducted a genome-wide association study using WGS data from the Long Life Family Study and identified a novel longevity-associated variant rs6543176 in the SLC9A2 gene. This SNP also showed a significant association with reduced hypertension risk and an increased, though not statistically significant, cancer risk. The association with cancer risk was replicated in the UK Biobank and FinnGen. Metabolomic analyses linked the rs6543176 longevity allele to higher serine levels, potentially associated with delayed mortality. Our findings warrant further investigation of SLC9A2’s role in both longevity and cancer susceptibility, and they highlight the need for careful evaluation in developing anti-aging therapies based on EL-associated alleles.

Objective:Cognitive impairment is associated with language changes that may be elicited from verbal responses during neuropsychological assessments that are not captured in traditional scoring. The current study investigated the utility of a linguistic analysis of paragraph recall responses for differentiating participants with and without cognitive impairment. Methods:Digital voice recordings of Logical Memory (LM) were available from 598 participants from the Long Life Family Study with normal cognition and 112 with cognitive impairment. Linguistic polyfeature scores for immediate (PFS-IR) and delayed recall (PFS-DR) were created from a weighted sum of features associated with cognitive impairment. Logistic regression models assessed the predictive value of each PFS and demographics for classifying cognitive impairment. Repeated measures models with Generalized Estimating Equations assessed whether PFSs predict decline on a cognitive screener. Results:Both immediate and delayed PFSs were significantly associated with cognitive status (PFS-IR β = 0.05, p<.001; PFS-DR β = 0.07, p<.001). A classifier with PFS-DR and demographics closely approximated the accuracy of the traditional LM score and demographics (AUC-PR = 0.81 vs 0.84, respectively). A higher PFS-DR was also associated with greater cognitive decline over an average of 5 years of follow-up (β = -0.08, p<.001). Conclusion:Quantification of linguistic features from paragraph recall using a linguistic PFS provides sufficient information for detecting cognitive impairment and predicting incident cognitive decline. The linguistic PFS has the potential to be integrated into automated testing, recording, and scoring pipelines allowing for the implementation of sensitive neuropsychological assessments in broader clinical and research settings.

We constructed a polygenic protective score specific to Alzheimer’s disease (AD PPS) based on the current literature among the participants enrolled in five studies of healthy aging and extreme longevity in the USA, Europe, and Asia. This AD PPS did not include variants on apolipoprotein E (APOE) gene. Comparisons of AD PPS in different data sets of healthy agers and centenarians showed that centenarians have stronger genetic protection against AD compared to individuals without familial longevity. The current study also shows evidence that this genetic protection increases with increasingly older ages in centenarians (centenarians who died before reaching age 105 years, semi-supercentenarians who reached age 105 to 109 years, and supercentenarians who reached age 110 years and older). However, the genetic protection was of modest size: the average increase in AD PPS was approximately one additional protective allele per 5 years of gained lifetime. Additionally, we show that the higher AD PPS was associated with better cognitive function and decreased mortality. Taken together, this analysis suggests that individuals who achieve the most extreme ages, on average, have the greatest protection against AD. This finding is robust to different genetic backgrounds with important implications for universal applicability of therapeutics that target this AD PPS.

Alternative splicing regulates transcript diversity and is increasingly recognized as a key mechanism in aging and age-related disease, yet little is known about how splicing contributes to human exceptional longevity. We analyzed RNA-seq data from the Integrative Longevity Omics (ILO) cohort, which includes centenarians (the oldest-old, age ≥100) and older adult controls (ages 60–89), to identify age-associated splicing events. Splicing was quantified with rMATS to estimate percent-spliced-in (PSI) values across five event categories, and quasi-binomial regression was used to model splicing changes with age. This analysis identified 731 significant age-associated events (false discovery rate < 0.05), the majority of which were mutually exclusive exons and skipped exons. A strong example is a skipped exon in Nuclear Transcription Factor Y subunit C (NFYC), a regulator of senescence-associated pathways. In controls, NFYC PSI trended downward with age, whereas in centenarians, PSI increased significantly with age, suggesting a reversal of midlife splicing trajectories. Residual analysis comparing observed PSI to predictions from a spline model of normal aging further suggests that centenarians deviate from normal aging patterns. This work describes age-associated splicing events in a population enriched for centenarians and provides preliminary evidence for a candidate splicing signature of exceptional longevity. Ongoing analyses will evaluate functional pathways and clinical relevance in independent cohorts.

Glycated hemoglobin A1c (HbA1c) indicates average glucose levels over three months and is associated with insulin resistance and type 2 diabetes (T2D). Longitudinal change in circulating HbA1c (ΔHbA1c) are also associated with aging processes, cognitive performance, and mortality. We analyzed ΔHbA1c in 1,886 non-diabetic Europeans from the Long Life Family Study (LLFS) to uncover gene loci influencing ΔHbA1c. Using growth curve modeling adjusted for multiple covariates, we derived ΔHbA1c and conducted linkage-guided sequence analysis. Our genome-wide linkage scan identified a significant locus on 17p12. In-depth analysis revealed a gene locus ARHGAP44 (rs56340929, explaining 27% of the linkage peak) that was significantly associated with ΔHbA1c. Interestingly, RNA transcription of ARHGAP44 was also significantly associated with ΔHbA1c in the LLFS, and this discovery was replicable on the gene level in the Framingham Offspring Study (FOS). Taking together, we successfully identified a novel gene locus ARHGAP44 for ΔHbA1c in family members without T2D. Further follow-up studies using longitudinal omics data in large independent cohorts are warranted.