Effects from medications on functional biomarkers of aging in three longitudinal studies of aging in Sweden.

Antihypertensive, lipid-lowering, and blood glucose-lowering drugs have slowed down the aging process in animal models. In humans, studies are limited, have short follow-up times, and show mixed results. Therefore, this study aimed to estimate the effects of commonly used medications on functional aging, cognitive function, and frailty. We included information on individuals from three Swedish longitudinal population-based studies collected between 1986 and 2014. Our exposures were the 21 most used groups of medications among individuals aged 65 years and older in the Swedish population in 2022. Functional aging index (n = 1191), cognitive function (n = 1094), and frailty index (n = 1361) were the outcomes of interest. To estimate the medication effects, we used a self-controlled analysis, where each individual is his/her own control, thereby adjusting for all time-stable confounders. The analysis was additionally adjusted for time-varying confounders (chronological age, Charlson Comorbidity Index, smoking, body mass index, and the number of drugs). The participants were 65.5-82.8 years at the first in-person assessment. Adrenergics/inhalants (effect size = 0.089) and lipid-modifying agents/plain (effect size = 0.082) were associated with higher values of cognitive function (improvement), and selective calcium channel blockers with mainly vascular effects (effect size = -0.129) were associated with lower values of the functional aging index (improvement). No beneficial effects were found on the frailty index. Adrenergics/inhalants, lipid-modifying agents/plain, and selective calcium channel blockers with mainly vascular effects may benefit functional biomarkers of aging. More research is needed to investigate their clinical value in preventing adverse aging outcomes.

Epigenome-wide analysis of frailty: Results from two European twin cohorts.

Epigenetics plays an important role in the aging process, but it is unclear whether epigenetic factors also influence frailty, an age-related state of physiological decline. In this study, we performed a meta-analysis of epigenome-wide association studies in four samples drawn from the Swedish Adoption/Twin Study of Aging (SATSA) and the Longitudinal Study of Aging Danish Twins (LSADT) to explore the association between DNA methylation and frailty. Frailty was defined using the frailty index (FI), and DNA methylation levels were measured in whole blood using Illumina's Infinium HumanMethylation450K and MethylationEPIC arrays. In the meta-analysis consisting of a total of 829 participants, we identified 589 CpG sites that were statistically significantly associated with either the continuous or categorical FI (false discovery rate <0.05). Many of these CpGs have previously been associated with age and age-related diseases. The identified sites were also largely directionally consistent in a longitudinal analysis using mixed-effects models in SATSA, where the participants were followed up to a maximum of 20 years. Moreover, we identified three differentially methylated regions within the MGRN1, MIR596, and TAPBP genes that have been linked to neuronal aging, tumor growth, and immune functions. Furthermore, our meta-analysis results replicated 34 of the 77 previously reported frailty-associated CpGs at p < 0.05. In conclusion, our findings demonstrate robust associations between frailty and DNA methylation levels in 589 novel CpGs, previously unidentified for frailty, and strengthen the role of neuronal/brain pathways in frailty.

Associations between Sleep Disorders and Impulsive-Compulsive Behaviors in Parkinson's Disease: A Prospective Cohort Study.

OBJECTIVE: To examine the associations of excessive daytime sleepiness (EDS) and probable rapid eye movement sleep behavior disorder (pRBD), respectively, with impulsive-compulsive behaviors (ICB) over a 5-year follow-up in patients with early Parkinson's disease (PD). METHODS: The Parkinson's Progression Markers Initiative is a multicenter cohort study based on an ongoing and open-ended registry. Longitudinal associations of sleep disorders with ICB over 5-year follow-up visits were estimated using generalized linear mixed-effects models among PD participants. RESULTS: A total of 825 PD participants were enrolled at baseline. The study sample had a median baseline age of 63.1 (interquartile range [IQR]: 55.6-69.3) years and comprised 496 (61.5%) men. Among them, 201 (24.9%) had ICB at baseline. In the generalized mixed-effects models, EDS (odds ratio [OR] =1.09, 95% confidence interval [CI] 1.05, 1.12) and RBD (OR=1.07, 95% CI 1.03, 1.12) were substantially associated with higher odds of developing ICB over time in PD patients, after multivariate adjustment including age, gender, family history, GDS score, STAI-Y score, MDS-UPDRS part III score, LEDD, and disease duration. Consistent results were observed when stratifying by age at baseline, gender, and PD family history. CONCLUSIONS: The study findings suggest a longitudinal association between EDS and pRBD with an increased risk of developing ICB in patients with Parkinson's disease. The findings emphasize the significance of evaluating and addressing sleep disorders in PD patients as a potential approach to managing ICB.

Genetically determined telomere length and its association with chronic obstructive pulmonary disease and interstitial lung disease in biobank Japan: A Mendelian randomization study.

Importance: Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) have been linked to shorter telomere length (TL). While understanding this association has critical clinical implications for respiratory diseases, previous studies exploring these associations were conducted in European populations. The present study aims to investigate this relationship in an Asian population. Objective: To examine the causal relationship between leukocyte TL and COPD and ILD in an Asian population. Design: Setting, and Participants: We used a genome-wide association study summary statistics-based two-sample Mendelian randomization (MR) design to investigate the association between leukocyte TL, genetically predicted by nine single-nucleotide polymorphisms and the risk of COPD and ILD. Participants were Japanese individuals enrolled in the Biobank Japan Project, including 3315 COPD patients and 806 ILD patients. Exposure: Leukocyte TL was genetically predicted by nine single-nucleotide polymorphisms. Results: The inverse-variance weighted estimates showed a significant inverse association between leukocyte TL and COPD (odds ratio [OR] = 0.78; 95 % confidence interval [CI]: 0.64, 0.95; P = 0.01) and ILD (OR = 0.29; 95 % CI: 0.14, 0.61; P = 0.001), respectively. All sensitivity analyses yielded consistent results. The MR-Egger regression intercept test showed no evidence of horizontal pleiotropy (Pintercept: COPD, 0.56; ILD: 0.70). Conclusion: and Relevance: Our findings suggest that leukocyte telomere shortening may causally increase the risk of COPD and ILD. These results highlight the potential importance of TL for these respiratory diseases.

Conversions between metabolically unhealthy and healthy obesity from midlife to late-life.

INTRODUCTION: Metabolically healthy obesity may be a transient phenotype, but studies with long follow-up, especially covering late-life, are lacking. We describe conversions between cross-categories of body mass index (BMI) and metabolic health in 786 Swedish twins with up to 27 years of follow-up, from midlife to late-life. METHODS: Metabolic health was defined as the absence of metabolic syndrome (MetS). We first visualized conversions between BMI-metabolic health phenotypes in 100 individuals with measurements available at ages 50-64, 65-79, and ≥80. Next, we modeled conversion in metabolic health status by BMI category in the full sample using Cox proportional hazards regression. RESULTS: The proportion of individuals with MetS and with overweight or obesity increased with age. However, one-fifth maintained a metabolically healthy overweight or obesity across all three age categories. Among those metabolically healthy at baseline, 59% converted to MetS during follow-up. Conversions occurred 56% more often among individuals with metabolically healthy obesity, but not overweight, compared to normal weight. Among those with MetS at baseline, 60% regained metabolic health during follow-up, with no difference between BMI categories. CONCLUSIONS: Conversions between metabolically healthy and unhealthy status occurred in both directions in all BMI categories. While conversions to MetS were more common among individuals with obesity, many individuals maintained or regained metabolic health during follow-up.

Dementia and mortality in older adults: A twin study.

INTRODUCTION: Dementia predicts increased mortality. We used case-control and co-twin control models to investigate genetic and shared environmental influences on this association. METHODS: Case-control design, including 987 twins with dementia and 2938 age- and sex-matched controls in the Swedish Twin Registry. Co-twin control design, including 90 monozygotic (MZ) and 288 dizygotic (DZ) twin pairs discordant for dementia. To test for genetic and environmental confounding, differences were examined in mortality risk between twins with dementia and their matched or co-twin controls. RESULTS: Twins with dementia showed greater mortality risk than age- and sex-matched controls (HR = 2.02 [1.86, 2.18]). Mortality risk is significantly elevated but attenuated substantially in discordant twin pairs, for example, comparing MZ twins with dementia to their co-twin controls (HR = 1.48 [1.08, 2.04]). DISCUSSION: Findings suggest that genetic factors partially confound the association between dementia and mortality and provide an alternative hypothesis to increased mortality due to dementia itself. Highlights We studied dementia and mortality in twin pairs discordant for dementia. People without dementia outlived people with dementia. Identical twins with dementia and their co-twin controls had similar survival time. Findings suggest genotype may explain the link between dementia and mortality.

Associations between psychological resilience and epigenetic clocks in the health and retirement study.

The aim of this study was to evaluate the associations between psychological resilience and epigenetic clocks assessed by DNA methylation age predictions. We used data from 4018 participants in the Health and Retirement Study. Multivariable linear regression models were used to estimate the association between psychological resilience and epigenetic clocks adjusted for age, sex, race, body mass index, smoking status, and years of education. Thirteen epigenetic clocks were used in our analysis and were highly correlated with one another. A higher psychological resilience score was associated with slower DNA methylation age acceleration for the majority of epigenetic clocks after multivariable adjustment. These findings imply that people with a higher level of psychological resilience may experience slower DNA methylation age acceleration and biological aging.

Educational Influences on Late-Life Health: Genetic Propensity and Attained Education.

OBJECTIVES: The educational gradient in late-life health is well established. Despite this, there are still ambiguities concerning the role of underlying confounding by genetic influences and gene-environment (GE) interplay. Here, we investigate the role of educational factors (attained and genetic propensities) on health and mortality in late life using genetic propensity for educational attainment (as measured by a genome-wide polygenic score, PGSEdu) and attained education. METHODS: By utilizing genetically informative twin data from the Swedish Twin Registry (n = 14,570), we investigated influences of the educational measures, familial confounding as well as the possible presence of passive GE correlation on both objective and subjective indicators of late-life health, that is, the Frailty Index, Multimorbidity, Self-rated health, cardiovascular disease, and all-cause mortality. RESULTS: Using between-within models to adjust for shared familial factors, we found that the relationship between educational level and health and mortality later in life persisted despite controlling for familial confounding. PGSEdu and attained education both uniquely predicted late-life health and mortality, even when mutually adjusted. Between-within models of PGSEdu on the health outcomes in dizygotic twins showed weak evidence for passive GE correlation (prGE) in the education-health relationship. DISCUSSION: Both genetic propensity to education and attained education are (partly) independently associated with health in late life. These results lend further support for a causal education-health relationship but also raise the importance of genetic contributions and GE interplay.

Interplay of body mass index and metabolic syndrome: association with physiological age from midlife to late-life.

Obesity and metabolic syndrome (MetS) share common pathophysiological characteristics with aging. To better understand their interplay, we examined how body mass index (BMI) and MetS jointly associate with physiological age, and if the associations changed from midlife to late-life. We used longitudinal data from 1,825 Swedish twins. Physiological age was measured as frailty index (FI) and functional aging index (FAI) and modeled independently in linear mixed-effects models adjusted for chronological age, sex, education, and smoking. We assessed curvilinear associations of BMI and chronological age with physiological age, and interactions between BMI, MetS, and chronological age. We found a significant three-way interaction between BMI, MetS, and chronological age on FI (p-interaction = 0·006), not FAI. Consequently, we stratified FI analyses by age: < 65, 65-85, and ≥ 85 years, and modeled FAI across ages. Except for FI at ages ≥ 85, BMI had U-shaped associations with FI and FAI, where BMI around 26-28 kg/m2 was associated with the lowest physiological age. MetS was associated with higher FI and FAI, except for FI at ages < 65, and modified the BMI-FI association at ages 65-85 (p-interaction = 0·02), whereby the association between higher BMI levels and FI was stronger in individuals with MetS. Age modified the MetS-FI association in ages ≥ 85, such that it was stronger at higher ages (p-interaction = 0·01). Low BMI, high BMI, and metabolic syndrome were associated with higher physiological age, contributing to overall health status among older individuals and potentially accelerating aging.

Temporal dynamics of epigenetic aging and frailty from midlife to old age.

BACKGROUND: DNA methylation-derived epigenetic clocks and frailty are well-established biological age measures capturing different aging processes. However, whether they are dynamically linked to each other across chronological age remains poorly understood. METHODS: This analysis included 1,309 repeated measurements in 524 individuals aged 50 to 90 years from the Swedish Adoption/Twin Study of Aging. Frailty was measured using a validated 42-item frailty index (FI). Five epigenetic clocks were calculated, including four principal component (PC)-based clocks trained on chronological age (PCHorvathAge, PCHannumAge) and aging-related physiological conditions (PCPhenoAge, PCGrimAge), and a pace of aging clock (DunedinPACE). Using dual change score models, we examined the dynamic, bidirectional associations between each of the epigenetic clocks and the FI over age to test for potential causal associations. RESULTS: The FI exhibited a nonlinear, accelerated increase across the older adulthood, whereas the epigenetic clocks mostly increased linearly with age. For PCHorvathAge, PCHannumAge, PCPhenoAge, and PCGrimAge, their associations with the FI were primarily due to correlated levels at age 50 but with no evidence of a dynamic longitudinal association. In contrast, we observed a unidirectional association between DunedinPACE and the FI, where a higher DunedinPACE predicted a subsequent increase in the FI, but not vice versa. CONCLUSION: Our results highlight a temporal order between epigenetic aging and frailty such that changes in DunedinPACE precede changes in the FI. This potentially suggests that the pace of aging clock can be used as an early marker of the overall physiological decline at system level.

Advanced biological ageing predicts future risk for neurological diagnoses and clinical examination findings.

Age is a dominant risk factor for some of the most common neurological diseases. Biological ageing encompasses interindividual variation in the rate of ageing and can be calculated from clinical biomarkers or DNA methylation data amongst other approaches. Here, we tested the hypothesis that a biological age greater than one's chronological age affects the risk of future neurological diagnosis and the development of abnormal signs on clinical examination. We analysed data from the Swedish Adoption/Twin Study of Aging (SATSA): a cohort with 3175 assessments of 802 individuals followed-up over several decades. Six measures of biological ageing were generated: two physiological ages (created from bedside clinical measurements and standard blood tests) and four blood methylation age measures. Their effects on future stroke, dementia or Parkinson's disease diagnosis, or development of abnormal clinical signs, were determined using survival analysis, with and without stratification by twin pairs. Older physiological ages were associated with ischaemic stroke risk; for example one standard deviation advancement in baseline PhenoAgePhys or KDMAgePhys residual increased future ischaemic stroke risk by 29.2% [hazard ratio (HR): 1.29, 95% confidence interval (CI) 1.06-1.58, P = 0.012] and 42.9% (HR 1.43, CI 1.18-1.73, P = 3.1 × 10-4), respectively. In contrast, older methylation ages were more predictive of future dementia risk, which was increased by 29.7% (HR 1.30, CI 1.07-1.57, P = 0.007) per standard deviation advancement in HorvathAgeMeth. Older physiological ages were also positively associated with future development of abnormal patellar or pupillary reflexes, and the loss of normal gait. Measures of biological ageing can predict clinically relevant pathology of the nervous system independent of chronological age. This may help to explain variability in disease risk between individuals of the same age and strengthens the case for trials of geroprotective interventions for people with neurological disorders.

Genetically and environmentally predicted obesity in relation to cardiovascular disease: a nationwide cohort study.

Background: Evidence indicates that the adverse health effects of obesity differ between genetically and environmentally influenced obesity. We examined differences in the association between obesity and cardiovascular disease (CVD) between individuals with a genetically predicted low, medium, or high body mass index (BMI). Methods: We used cohort data from Swedish twins born before 1959 who had BMI measured between the ages of 40-64 years (midlife) or at the age of 65 years or later (late-life), or both, and prospective CVD information from nationwide register linkage through 2016. A polygenic score for BMI (PGSBMI) was used to define genetically predicted BMI. Individuals missing BMI or covariate data, or diagnosed with CVD at first BMI measure, were excluded, leaving an analysis sample of 17,988 individuals. We applied Cox proportional hazard models to examine the association between BMI category and incident CVD, stratified by the PGSBMI. Co-twin control models were applied to adjust for genetic influences not captured by the PGSBMI. Findings: Between 1984 and 2010, the 17,988 participants were enrolled in sub-studies of the Swedish Twin Registry. Midlife obesity was associated with a higher risk of CVD across all PGSBMI categories, but the association was stronger with genetically predicted lower BMI (hazard ratio from 1.55 to 2.08 for those with high and low PGSBMI, respectively). Within monozygotic twin pairs, the association did not differ by genetically predicted BMI, indicating genetic confounding not captured by the PGSBMI. Results were similar when obesity was measured in late-life, but suffered from low power. Interpretation: Obesity was associated with CVD regardless of PGSBMI category, but obesity influenced by genetic predisposition (genetically predicted high BMI) was less harmful than obesity influenced by environmental factors (obesity despite genetically predicted low BMI). However, additional genetic factors, not captured by the PGSBMI, still influence the associations. Funding: The Strategic Research Program in Epidemiology at Karolinska Institutet; Loo and Hans Osterman's Foundation; Foundation for Geriatric Diseases at Karolinska Institutet; the Swedish Research Council for Health, Working Life and Welfare; the Swedish Research Council; and the National Institutes of Health.

Influences of genetically predicted and attained education on geographic mobility and their association with mortality.

INTRODUCTION: Both educational attainment and genetic propensity to education (PGSEdu) have been associated with geographic mobility. Socioeconomic conditions are, in turn, associated with individuals' health. Geographic mobility could therefore lead to better health for some since it could provide better opportunities, like education. Our aim was to study how attained education and genetic predisposition for higher education are related to geographic mobility, and how they affect the association between geographic mobility and mortality. METHODS: We used data from the Swedish Twin Registry (twins born 1926-1955; n = 14,211) in logistic regression models to test if attained education and PGSEdu predicted geographic mobility. Cox regression models were then performed to test if geographic mobility, attained education, and PGSEdu were associated with mortality. RESULTS: The results show that both attained education and PGSEdu predicted geographic mobility, in both independent and joint effect models, with higher education associated with higher mobility. Geographic mobility was associated with lower mortality in the independent effect model, but joint effect models showed that this association was completely explained by attained education. CONCLUSIONS: To conclude, both attained education and PGSEdu were associated with geographic mobility. Moreover, attained education explained the relationship between geographic mobility and mortality.

Leukocyte DNA methylation in Alzheimer´s disease associated genes: replication of findings from neuronal cells.

Differences in gene-wide DNA methylation of the Alzheimer's disease (AD)-associated genes BIN1, HLA-DRB5, SORL1, SLC24A4, and ABCA7 are reported to be associated with AD in post-mortem brain samples. We investigated whether the same associations could be found in leukocytes collected pre-mortem. Using cohort data of 544 Swedish twins (204 dementia diagnoses), we replicated the findings in HLA-DRB5 and SLC24A4 at P < 0.05. However, co-twin control analyses indicated that the associations were partly explained by familial confounding. Thus, DNA methylation differences in HLA-DRB5 and SLC24A4 are present in both neuronal cells and leukocytes, and not fully explained familial factors.

Adiposity and the risk of dementia: mediating effects from inflammation and lipid levels.

While midlife adiposity is a risk factor for dementia, adiposity in late-life appears to be associated with lower risk. What drives the associations is poorly understood, especially the inverse association in late-life. Using results from genome-wide association studies, we identified inflammation and lipid metabolism as biological pathways involved in both adiposity and dementia. To test if these factors mediate the effect of midlife and/or late-life adiposity on dementia, we then used cohort data from the Swedish Twin Registry, with measures of adiposity and potential mediators taken in midlife (age 40-64, n = 5999) or late-life (age 65-90, n = 7257). Associations between body-mass index (BMI), waist-hip ratio (WHR), C-reactive protein (CRP), lipid levels, and dementia were tested in survival and mediation analyses. Age was used as the underlying time scale, and sex and education included as covariates in all models. Fasting status was included as a covariate in models of lipids. One standard deviation (SD) higher WHR in midlife was associated with 25% (95% CI 2-52%) higher dementia risk, with slight attenuation when adjusting for BMI. No evidence of mediation through CRP or lipid levels was present. After age 65, one SD higher BMI, but not WHR, was associated with 8% (95% CI 1-14%) lower dementia risk. The association was partly mediated by higher CRP, and suppressed when high-density lipoprotein levels were low. In conclusion, the negative effects of midlife adiposity on dementia risk were driven directly by factors associated with body fat distribution, with no evidence of mediation through inflammation or lipid levels. There was an inverse association between late-life adiposity and dementia risk, especially where the body's inflammatory response and lipid homeostasis is intact.

Polygenic resilience scores capture protective genetic effects for Alzheimer's disease.

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Independent and joint effects of body mass index and metabolic health in mid- and late-life on all-cause mortality: a cohort study from the Swedish Twin Registry with a mean follow-up of 13 Years.

BACKGROUND: There is robust evidence that in midlife, higher body mass index (BMI) and metabolic syndrome (MetS), which often co-exist, are associated with increased mortality risk. However, late-life findings are inconclusive, and few studies have examined how metabolic health status (MHS) affects the BMI-mortality association in different age categories. We, therefore, aimed to investigate how mid- and late-life BMI and MHS interact to affect the risk of mortality. METHODS: This cohort study included 12,467 participants from the Swedish Twin Registry, with height, weight, and MHS measures from 1958-2008 and mortality data linked through 2020. We applied Cox proportional hazard regression with age as a timescale to examine how BMI categories (normal weight, overweight, obesity) and MHS (identification of MetS determined by presence/absence of hypertension, hyperglycemia, low HDL, hypertriglyceridemia), independently and in interaction, are associated with the risk of all-cause mortality. Models were adjusted for sex, education, smoking, and cardiovascular disease. RESULTS: The midlife group included 6,252 participants with a mean age of 59.6 years (range = 44.9-65.0) and 44.1% women. The late-life group included 6,215 participants with mean age 73.1 years (65.1-95.3) and 46.6% women. In independent effect models, metabolically unhealthy status in midlife increased mortality risks by 31% [hazard ratio 1.31; 95% confidence interval 1.12-1.53] and in late-life, by 18% (1.18;1.10-1.26) relative to metabolically healthy individuals. Midlife obesity increased the mortality risks by 30% (1.30;1.06-1.60) and late-life obesity by 15% (1.15; 1.04-1.27) relative to normal weight. In joint models, the BMI estimates were attenuated while those of MHS were less affected. Models including BMI-MHS categories revealed that, compared to metabolically healthy normal weight, the metabolically unhealthy obesity group had increased mortality risks by 53% (1.53;1.19-1.96) in midlife, and across all BMI categories in late-life (normal weight 1.12; 1.01-1.25, overweight 1.10;1.01-1.21, obesity 1.31;1.15-1.49). Mortality risk was decreased by 9% (0.91; 0.83-0.99) among those with metabolically healthy overweight in late-life. CONCLUSIONS: MHS strongly influenced the BMI-mortality association, such that individuals who were metabolically healthy with overweight or obesity in mid- or late-life did not carry excess risks of mortality. Being metabolically unhealthy had a higher risk of mortality independent of their BMI.

Measuring heritable contributions to Alzheimer's disease: polygenic risk score analysis with twins.

The heritability of Alzheimer's disease estimated from twin studies is greater than the heritability derived from genome-based studies, for reasons that remain unclear. We apply both approaches to the same twin sample, considering both Alzheimer's disease polygenic risk scores and heritability from twin models, to provide insight into the role of measured genetic variants and to quantify uncaptured genetic risk. A population-based heritability and polygenic association study of Alzheimer's disease was conducted between 1986 and 2016 and is the first study to incorporate polygenic risk scores into biometrical twin models of Alzheimer's disease. The sample included 1586 twins drawn from the Swedish Twin Registry which were nested within 1137 twin pairs (449 complete pairs and 688 incomplete pairs) with clinically based diagnoses and registry follow-up (M age = 85.28, SD = 7.02; 44% male; 431 cases and 1155 controls). We report contributions of polygenic risk scores at P < 1 × 10-5, considering a full polygenic risk score (PRS), PRS without the APOE region (PRS.no.APOE) and PRS.no.APOE plus directly measured APOE alleles. Biometric twin models estimated the contribution of environmental influences and measured (PRS) and unmeasured genes to Alzheimer's disease risk. The full PRS and PRS.no.APOE contributed 10.1 and 2.4% to Alzheimer's disease risk, respectively. When APOE ɛ4 alleles were added to the model with the PRS.no.APOE, the total contribution was 11.4% to Alzheimer's disease risk, where APOE ɛ4 explained 9.3% and PRS.no.APOE dropped from 2.4 to 2.1%. The total genetic contribution to Alzheimer's disease risk, measured and unmeasured, was 71% while environmental influences unique to each twin accounted for 29% of the risk. The APOE region accounts for much of the measurable genetic contribution to Alzheimer's disease, with a smaller contribution from other measured polygenic influences. Importantly, substantial background genetic influences remain to be understood.