Can we rely on magnetic resonance imaging for prostate cancer detection and surgical planning? Comprehensive analysis of a large cohort of patients undergoing transperineal mapped biopsies.

PURPOSE: To evaluate MRI and histological concordance in prostate cancer (PCa) identification via mapped transperineal biopsies. METHODOLOGY: Retrospective per-lesion analysis of patients undergoing MRI and transperineal biopsy at the Valencian Institute of Oncology (2016-2024) using CAPROSIVO PCa data. Patients underwent MRI, with or without regions of interest (ROI), followed by transperineal biopsies (3-5 cores/ROI, 20-30 systematic). Sensitivity (Se), specificity (Sp), negative predictive value (NPV), positive predictive value (PPV), and area under the curve (AUC) were calculated, considering PI-RADS 3 lesions as positive or negative. Gleason Grade Group (GG) > 1 defined clinically significant PCa (csPCa). RESULTS: 1817 lesions were analyzed from 1325 patients (median age 67, median PSA 6.3 ng/ml). 53% MRI were negative, GG > 1 prevalence was 38.4%. MRI-negative cases showed varying PCa rates: 57.4% negative, 30.2% GG 1, and 12.4% GG > 1. PI-RADS 3 lesions had mixed outcomes: 45.6% benign, 13.1% GG 1, and 41.3% GG > 1. 9.2% PI-RADS 4-5 lesions were negative, 9% GG 1, and 81.7% GG > 1. For PI-RADS 3 lesions considered positive, Se, Sp, NPV, PPV, and AUC were 82.9%, 75%, 87.6%, 67.4%, and 0.79 respectively. Considering PI-RADS 3 as negative yielded 64.8% Se, 91% Sp, 80.6% NPV, 81.7% PPV, and 0.78 AUC. CONCLUSION: MRI and mapped prostate biopsies exhibited moderate concordance. MRI could miss up to one in five csPCa foci and misinterpret one in three ROIs. Careful MRI interpretation is crucial for optimizing patient care.

AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease.

Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and intervention strategies. We developed a state-of-the-art deep learning autoencoder survival analysis model (AESurv) to effectively analyze high-dimensional blood DNA methylation features and traditional clinical risk factors by learning low-dimensional representation of participants for time-to-event CHD prediction. We demonstrated the utility of our model in two cohort studies: the Strong Heart Study cohort (SHS), a prospective cohort studying cardiovascular disease and its risk factors among American Indians adults; the Women's Health Initiative (WHI), a prospective cohort study including randomized clinical trials and observational study to improve postmenopausal women's health with one of the main focuses on cardiovascular disease. Our AESurv model effectively learned participant representations in low-dimensional latent space and achieved better model performance (concordance index-C index of 0.864 ± 0.009 and time-to-event mean area under the receiver operating characteristic curve-AUROC of 0.905 ± 0.009) than other survival analysis models (Cox proportional hazard, Cox proportional hazard deep neural network survival analysis, random survival forest, and gradient boosting survival analysis models) in the SHS. We further validated the AESurv model in WHI and also achieved the best model performance. The AESurv model can be used for accurate CHD prediction and assist health care professionals and patients to perform early intervention strategies. We suggest using AESurv model for future time-to-event CHD prediction based on DNA methylation features.

Comparative evaluation of continence and potency after radical prostatectomy: Robotic vs. laparoscopic approaches, validating LAP-01 trial.

BACKGROUND: Minimally invasive techniques have demonstrated several advantages over the open approach. In the field of prostate cancer, the LAP-01 trial demonstrated the superiority of robotic-assisted radical prostatectomy (RARP) over laparoscopic radical prostatectomy (LRP) when comparing continence at 3-month after surgery, with no statistically significant differences at 6 and 12 months of follow-up. OBJECTIVES: Externally validate the LAP-01 study and compare functional outcomes between the two minimally invasive approaches. MATERIAL AND METHODS: This retrospective study, conducted by a single surgeon (MRB), utilized data from a prospectively collected database, which included patients who underwent both RARP or LRP. Data regarding baseline characteristics, continence (assessed through the 24-h Pad test and ICIQ questionnaire) and potency were collected at multiple time points: 1 and 6 weeks after catheter removal, 3-, 6-, and 12-months post-surgery. RESULTS: The study encompasses 601 patients, 455 who underwent LRP and 146 RARP. The median age at diagnosis was 64 for LRP and 62 for RARP, while the median PSA levels at diagnosis were 6.7 ng/mL for LRP and 6.5 ng/mL for RARP. Bilateral nerve-sparing procedures were performed in 34.07 % of LRP cases and 51.37 % of RARP cases. RARP exhibited a significant advantage over LRP both in continence and potency. Continence rates at 3-, 6- and 9-month after radical prostatectomy (RP) were 36.43 %, 61.86 % and 79.87 % for LRP, compared to 50.98 %, 69.87 % and 91.69 % for RARP. Potency rates at the same intervals were 0.90 %, 3.16 % and 6.39 % for LRP, and 6.19 %, 9.16 % and 18.96 % for RARP. These rates were more pronounced in patients with bilateral nerve-sparing. CONCLUSION: Our study demonstrates that RARP results in significantly better continence recovery and superior potency outcomes throughout the entire follow-up period compared to LRP, even at the beginning of the robotic approach learning curve.

Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Relationships of depression and antidepressant use with epigenetic age acceleration and all-cause mortality among postmenopausal women.

We investigated relations of depressive symptoms, antidepressant use, and epigenetic age acceleration with all-cause mortality risk among postmenopausal women. Data were analyzed from ≤1,900 participants in the Women's Health Initiative study testing four-way decomposition models. After a median 20.4y follow-up, 1,161 deaths occurred. Approximately 11% had elevated depressive symptoms (EDS+), 7% were taking antidepressant medication at baseline (ANTIDEP+), while 16.5% fell into either category (EDS_ANTIDEP+). Baseline ANTIDEP+, longitudinal transition into ANTIDEP+ and accelerated epigenetic aging directly predicted increased mortality risk. GrimAge DNA methylation age acceleration (AgeAccelGrim) partially mediated total effects of baseline ANTIDEP+ and EDS_ANTIDEP+ on all-cause mortality risk in socio-demographic factors-adjusted models (Pure Indirect Effect >0, P < 0.05; Total Effect >0, P < 0.05). Thus, higher AgeAccelGrim partially explained the relationship between antidepressant use and increased all-cause mortality risk, though only prior to controlling for lifestyle and health-related factors. Antidepressant use and epigenetic age acceleration independently predicted increased all-cause mortality risk. Further studies are needed in varying populations.

Prostate cancer patients with lymphatic node involvement detected by immunohistochemistry. Is the effort worthwhile?

INTRODUCTION: Lymph node (LN) status is one of the main prognostic factors in localized prostate cancer (CaP) patients after surgery. Examining palpable lymph nodes with hematoxylin and eosin (HE) is the most common approach in clinical practice; however, immunohistochemistry (IHC) has been reported to increase the LN detection rate. We reviewed the oncological results of patients with LN metastasis detected by IHC. METHODS: Retrospective study of CaP patients who underwent lymphadenectomy at the time of the prostatectomy. Extended lymphadenectomy was performed with complementary indocyanine green (ICG) guidance. Three groups were considered according to LN status. Definition of the pN+ group was made if LNs were detected by HE, occulted lymph node-positive (OLN+) was considered when ≥ 1 LN was identified with IHC and occulted lymph node-negative (OLN-) if no metastatic nodes were found. Oncological outcomes were reported regarding PSA kinetics, biochemical recurrence (BCR), need for secondary treatments and metastasis-free survival (MFS). RESULTS: A total of 283 patients with a median follow-up of 69 months were included in the study. Immunohistochemical assessment revealed metastatic LNs in 8.9% of patients. The rate of locally advanced disease and positive surgical margins was higher in the OLN + and pN + groups vs the OLN - group (P < 0.05). At the end of follow-up, 19%, 44% and 52% of patients from the OLN -, OLN + and pN + groups experienced BCR (P < 0.001), respectively. Additionally, 2.6%, 17% and 22% of patients developed metastatic progression from the OLN -, OLN + and pN+ group (P < 0.001), respectively. In the multivariate analysis, the OLN + group had a higher risk HR: 12 (95% CI, 2.4-56; P = 0.002) of metastatic progression in comparison with OLN - patients. This difference was not observed in the risk of biochemical recurrence HR 1.8 (95% CI, 0.9-3.8; P = 0.09). CONCLUSION: Conventional HE histological analysis underdiagnosed nearly 10% of patients. IHC-detected patients were at higher risk of metastasis development than OLN - patients. This report highlights the importance of optimizing the anatomopathological analysis properly.

Plasma oxysterols are associated with serum lipids and dementia risk in older women.

INTRODUCTION: Apolipoprotein E4 (APOE4) carriers' tendency toward hypercholesterolemia may contribute to Alzheimer's disease (AD) risk through oxysterols, which traverse the blood-brain barrier. METHODS: Relationships between baseline plasma oxysterols, APOE status, serum lipids, and cognitive impairment risk were examined in 328 postmenopausal women from the Women's Health Initiative Memory Study. Women were followed for 25 years or until incident dementia or cognitive impairment. RESULTS: Levels of 24(S)-hydroxycholesterol (24-OHC), 27-hydroxycholesterol (27-OHC), and 24-OHC/27-OHC ratio did not differ by APOE status (p's > 0.05). Higher 24-OHC and 27-OHC were associated with higher total, low density lipoprotein (LDL), non-high density lipoprotein (HDL), remnant, LDL/HDL, and total/HDL cholesterol and triglycerides (p's < 0.05). Higher 24-OHC/27-OHC was associated with greater dementia risk (hazard ratio = 1.51, 95% confidence interval:1.02-2.22), which interaction analyses revealed as significant for APOE3 and APOE4+, but not APOE2+ carriers. DISCUSSION: Less favorable lipid profiles were associated with higher oxysterol levels. A higher ratio of 24-OHC/27-OHC may contribute to dementia risk in APOE3 and APOE4+ carriers.

20-year depressive symptoms, dementia, and structural neuropathology in older women.

INTRODUCTION: The course of depressive symptoms and dementia risk is unclear, as are potential structural neuropathological common causes. METHODS: Utilizing joint latent class mixture models, we identified longitudinal trajectories of annually assessed depressive symptoms and dementia risk over 21 years in 957 older women (baseline age 72.7 years old) from the Women's Health Initiative Memory Study. In a subsample of 569 women who underwent structural magnetic resonance imaging, we examined whether estimates of cerebrovascular disease and Alzheimer's disease (AD)-related neurodegeneration were associated with identified trajectories. RESULTS: Five trajectories of depressive symptoms and dementia risk were identified. Compared to women with minimal symptoms, women who reported mild and stable and emerging depressive symptoms were at the highest risk of developing dementia and had more cerebrovascular disease and AD-related neurodegeneration. DISCUSSION: There are heterogeneous profiles of depressive symptoms and dementia risk. Common neuropathological factors may contribute to both depression and dementia. Highlights The progression of depressive symptoms and concurrent dementia risk is heterogeneous. Emerging depressive symptoms may be a prodromal symptom of dementia. Cerebrovascular disease and AD are potentially shared neuropathological factors.

Deep phenotyping of dementia in a multi-ethnic cardiovascular cohort: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: Our understanding of the specific aspects of vascular contributions to dementia remains unclear. OBJECTIVES: We aim to identify the correlates of incident dementia in a multi-ethnic cardiovascular cohort. METHODS: A total of 6806 participants with follow-up data for incident dementia were included. Probable dementia diagnoses were identified using hospitalization discharge diagnoses according to the International Classification of Diseases Codes (ICD). We used Random Forest analyses to identify the correlates of incident dementia and cognitive function from among 198 variables collected at the baseline MESA exam entailing demographic risk factors, medical history, anthropometry, lab biomarkers, electrocardiograms, cardiovascular magnetic resonance imaging, carotid ultrasonography, coronary artery calcium and liver fat content. Death and stroke were considered competing events. RESULTS: Over 14 years of follow-up, 326 dementia events were identified. Beyond age, the top correlates of dementia included coronary artery calcification, high sensitivity troponin, common carotid artery intima to media thickness, NT-proBNP, physical activity, pulse pressure, tumor necrosis factor-α, history of cancer, and liver to spleen attenuation ratio from computed tomography. Correlates of cognitive function included income and physical activity, body size, serum glucose, glomerular filtration rate, measures of carotid artery stiffness, alcohol use, and inflammation indexed as IL-2 and TNF soluble receptors and plasmin-antiplasmin complex. CONCLUSION: In a deeply phenotyped cardiovascular cohort we identified the key correlates of dementia beyond age as subclinical atherosclerosis and myocyte damage, vascular function, inflammation, physical activity, hepatic steatosis, and history of cancer.

Subclinical vascular composites predict clinical cardiovascular disease, stroke, and dementia: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND AND AIMS: Subclinical cardiovascular disease (CVD) measures may reflect biological pathways that contribute to increased risk for coronary heart disease (CHD) events, stroke, and dementia beyond conventional risk scores. METHODS: The Multi-Ethnic Study of Atherosclerosis (MESA) followed 6814 participants (45-84 years of age) from baseline in 2000-2002 to 2018 over 6 clinical examinations and annual follow-up interviews. MESA baseline subclinical CVD procedures included: seated and supineblood pressure, coronary calcium scan, radial artery tonometry, and carotid ultrasound. Baseline subclinical CVD measures were transformed into z-scores before factor analysis to derive composite factor scores. Time to clinical event for all-cause CVD, CHD, stroke and ICD code-based dementia events were modeled using Cox proportional hazards models reported as area under the curve (AUC) with 95% Confidence Intervals (95%CI) at 10 and 15 years of follow-up. All models included all factor scores together, and adjustment for conventional risk scores for global CVD, stroke, and dementia. RESULTS: After factor selection, 24 subclinical measures aggregated into four distinct factors representing: blood pressure, atherosclerosis, arteriosclerosis, and cardiac factors. Each factor significantly predicted time to CVD events and dementia at 10 and 15 years independent of each other and conventional risk scores. Subclinical vascular composites of atherosclerosis and arteriosclerosis best predicted time to clinical events of CVD, CHD, stroke, and dementia. These results were consistent across sex and racial and ethnic groups. CONCLUSIONS: Subclinical vascular composites of atherosclerosis and arteriosclerosis may be useful biomarkers to inform the vascular pathways contributing to events of CVD, CHD, stroke, and dementia.

Associations of plasma proteomics and age-related outcomes with brain age in a diverse cohort.

Machine learning models are increasingly being used to estimate "brain age" from neuroimaging data. The gap between chronological age and the estimated brain age gap (BAG) is potentially a measure of accelerated and resilient brain aging. Brain age calculated in this fashion has been shown to be associated with mortality, measures of physical function, health, and disease. Here, we estimate the BAG using a voxel-based elastic net regression approach, and then, we investigate its associations with mortality, cognitive status, and measures of health and disease in participants from Atherosclerosis Risk in Communities (ARIC) study who had a brain MRI at visit 5 of the study. Finally, we used the SOMAscan assay containing 4877 proteins to examine the proteomic associations with the MRI-defined BAG. Among N = 1849 participants (age, 76.4 (SD 5.6)), we found that increased values of BAG were strongly associated with increased mortality and increased severity of the cognitive status. Strong associations with mortality persisted when the analyses were performed in cognitively normal participants. In addition, it was strongly associated with BMI, diabetes, measures of physical function, hypertension, prevalent heart disease, and stroke. Finally, we found 33 proteins associated with BAG after a correction for multiple comparisons. The top proteins with positive associations to brain age were growth/differentiation factor 15 (GDF-15), Sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SEVP 1), matrilysin (MMP7), ADAMTS-like protein 2 (ADAMTS), and heat shock 70 kDa protein 1B (HSPA1B) while EGF-receptor (EGFR), mast/stem-cell-growth-factor-receptor (KIT), coagulation-factor-VII, and cGMP-dependent-protein-kinase-1 (PRKG1) were negatively associated to brain age. Several of these proteins were previously associated with dementia in ARIC. These results suggest that circulating proteins implicated in biological aging, cellular senescence, angiogenesis, and coagulation are associated with a neuroimaging measure of brain aging.

Comparison of PM2.5 Air Pollution Exposures and Health Effects Associations Using 11 Different Modeling Approaches in the Women's Health Initiative Memory Study (WHIMS).

BACKGROUND: Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear. OBJECTIVES: Our objective is to compare particulate matter with aerodynamic diameter ≤2.5µm (PM2.5) concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses. METHODS: We assigned annual PM2.5 exposure estimates from 1999 to 2004 derived from 11 different approaches to Women's Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between PM2.5 and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region. RESULTS: With a few exceptions, relative agreement of approach-specific PM2.5 exposure estimates was high for PM2.5 concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near PM2.5 monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for PM2.5. There was no evidence of large differences in health effects associations with PM2.5 among estimation approaches in analyses adjusted for climate region. CONCLUSIONS: Different estimation approaches produced similar spatial patterns of PM2.5 concentrations across the contiguous US and in areas with dense monitoring data, and PM2.5-health effects associations were similar among estimation approaches. PM2.5 estimates and PM2.5-health effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about PM2.5 estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest. https://doi.org/10.1289/EHP12995.

Association of type 2 diabetes mellitus with dementia-related and non-dementia-related mortality among postmenopausal women: A secondary competing risks analysis of the women's health initiative.

INTRODUCTION: Alzheimer's disease (AD) and AD-related dementias (ADRD) are leading causes of death among older adults in the United States. Efforts to understand risk factors for prevention are needed. METHODS: Participants (n = 146,166) enrolled in the Women's Health Initiative without AD at baseline were included. Diabetes status was ascertained from self-reported questionnaires and deaths attributed to AD/ADRD from hospital, autopsy, and death records. Competing risk regression models were used to estimate the cause-specific hazard ratios (HRs) and 95% confidence intervals (CIs) for the prospective association of type 2 diabetes mellitus (T2DM) with AD/ADRD and non-AD/ADRD mortality. RESULTS: There were 29,393 treated T2DM cases and 8628 AD/ADRD deaths during 21.6 (14.0-23.5) median (IQR) years of follow-up. Fully adjusted HRs (95% CIs) of the association with T2DM were 2.94 (2.76-3.12) for AD/ADRD and 2.65 (2.60-2.71) for the competing risk of non-AD/ADRD mortality. DISCUSSION: T2DM is associated with AD/ADRD and non-AD/ADRD mortality. HIGHLIGHTS: Type 2 diabetes mellitus is more strongly associated with Alzheimer's disease (AD)/AD and related dementias (ADRD) mortality compared to the competing risk of non-AD/ADRD mortality among postmenopausal women. This relationship was consistent for AD and ADRD, respectively. This association is strongest among participants without obesity or hypertension and with younger age at baseline, higher diet quality, higher physical activity, higher alcohol consumption, and older age at the time of diagnosis of type 2 diabetes mellitus.

Alzheimer's Related Neurodegeneration Mediates Air Pollution Effects on Medial Temporal Lobe Atrophy.

Exposure to ambient air pollution, especially particulate matter with aerodynamic diameter <2.5 µm (PM2.5) and nitrogen dioxide (NO2), are environmental risk factors for Alzheimer's disease and related dementia. The medial temporal lobe (MTL) is an important brain region subserving episodic memory that atrophies with age, during the Alzheimer's disease continuum, and is vulnerable to the effects of cerebrovascular disease. Despite the importance of air pollution it is unclear whether exposure leads to atrophy of the MTL and by what pathways. Here we conducted a longitudinal study examining associations between ambient air pollution exposure and MTL atrophy and whether putative air pollution exposure effects resembled Alzheimer's disease-related neurodegeneration or cerebrovascular disease-related neurodegeneration. Participants included older women (n = 627; aged 71-87) who underwent two structural brain MRI scans (MRI-1: 2005-6; MRI-2: 2009-10) as part of the Women's Health Initiative Memory Study of Magnetic Resonance Imaging. Regionalized universal kriging was used to estimate annual concentrations of PM2.5 and NO2 at residential locations aggregated to 3-year averages prior to MRI-1. The outcome was 5-year standardized change in MTL volumes. Mediators included voxel-based MRI measures of the spatial pattern of neurodegeneration of Alzheimer's disease (Alzheimer's disease pattern similarity scores [AD-PS]) and whole-brain white matter small-vessel ischemic disease (WM-SVID) volume as a proxy of global cerebrovascular damage. Structural equation models were constructed to examine whether the associations between exposures with MTL atrophy were mediated by the initial level or concurrent change in AD-PS score or WM-SVID while adjusting for sociodemographic, lifestyle, clinical characteristics, and intracranial volume. Living in locations with higher PM2.5 (per interquartile range [IQR]=3.17µg/m3) or NO2 (per IQR=6.63ppb) was associated with greater MTL atrophy (ßPM2.5 = -0.29, 95% confidence interval [CI]=[-0.41,-0.18]; ßNO2 =-0.12, 95%CI=[-0.23,-0.02]). Greater PM2.5 was associated with larger increases in AD-PS (ßPM2.5 = 0.23, 95%CI=[0.12,0.33]) over time, which partially mediated associations with MTL atrophy (indirect effect= -0.10; 95%CI=[-0.15, -0.05]), explaining approximately 32% of the total effect. NO2 was positively associated with AD-PS at MRI-1 (ßNO2=0.13, 95%CI=[0.03,0.24]), which partially mediated the association with MTL atrophy (indirect effect= -0.01, 95% CI=[-0.03,-0.001]). Global WM-SVID at MRI-1 or concurrent change were not significant mediators between exposures and MTL atrophy. Findings support the mediating role of Alzheimer's disease-related neurodegeneration contributing to MTL atrophy associated with late-life exposures to air pollutants. Alzheimer's disease-related neurodegeneration only partially explained associations between exposure and MTL atrophy suggesting the role of multiple neuropathological processes underlying air pollution neurotoxicity on brain aging.

Associations of dietary cholesterol and fat, blood lipids, and risk for dementia in older women vary by APOE genotype.

INTRODUCTION: Whether apolipoprotein E's (APOE's) involvement in lipid metabolism contributes to Alzheimer's disease (AD) risk remains unknown. METHODS: Incident probable dementia and cognitive impairment (probable dementia+mild cognitive impairment) were analyzed in relation to baseline serum lipids (total, low-density lipoprotein [LDL], high-density lipoprotein [HDL], non-HDL cholesterol, total-to-HDL, LDL-to-HDL, remnant cholesterol, and triglycerides) using Mendelian randomization in 5358 postmenopausal women from the Women's Health Initiative Memory Study. We also examined associations of baseline dietary cholesterol and fat with lipids based on APOE status. RESULTS: After an average of 11.13 years, less favorable lipid levels related to greater dementia and cognitive impairment risk. Dementia (odds ratio [OR] = 3.13; 95% confidence interval [CI]: 2.31 to 4.24) and cognitive impairment (OR = 2.38; 95% CI: 1.85 to 3.06) risk were greatest in relation to higher remnant cholesterol levels. Greater cholesterol consumption related to poorer lipids in APOE4+ compared to APOE3 carriers. DISCUSSION: APOE4+ carriers consuming more cholesterol had less favorable lipids, which were associated with greater dementia and cognitive impairment risk. HIGHLIGHTS: Less favorable serum lipids were associated with higher dementia incidence. Mendelian randomization findings suggest causality between lipids and dementia. Lipid levels in older women may be clinical indicators of dementia risk. APOE4 carriers had poorest lipid profiles in relation to cholesterol consumption. APOE risk for dementia may be modifiable through lipid management.

Personalised indocyanine-guided lymphadenectomy for prostate cancer: a randomised clinical trial.

OBJECTIVES: To study the safety and efficacy of a personalised indocyanine-guided pelvic lymph node dissection (PLND) against extended PLND (ePLND) during radical prostatectomy (RP). PATIENTS AND METHODS: Patients who were candidates for RP and lymphadenectomy, with intermediate- or high-risk prostate cancer (PCa) according to the National Comprehensive Cancer Network guidelines, were enrolled in this randomised clinical trial. Randomisation was made 1:1 to indocyanine green (ICG)-PLND (only ICG-stained LNs) or ePLND (obturator fossa, external, internal, and common iliac and presacral LNs). The primary endpoint was the complication rate within 3 months after RP. Secondary endpoints included: rate of major complications (Clavien-Dindo Grade III-IV), time to drainage removal, length of stay, percentage of patients classified as pN1, number of LNs removed, number of metastatic LNs, rate of patients with undetectable prostate-specific antigen (PSA), biochemical recurrence (BCR)-free survival, and rate of patients with androgen-deprivation therapy at 24 months. RESULTS: A total of 108 patients were included with a median follow-up of 16 months. In all, 54 were randomised to ICG-PLND and 54 to ePLND. The postoperative complication rate was higher in the ePLND (70%) vs the ICG-PLND group (32%) (P < 0.001). Differences between major complications in both groups were not statically significant (P = 0.7). The pN1 detection rate was higher in the ICG-PLND group (28%) vs the ePLND group (22%); however, this difference was not statistically significant (P = 0.7). The rate of undetectable PSA at 12 months was 83% in the ICG-PLND vs 76% in the ePLND group, which was not statistically significant. Additionally, there were no statistically significant differences in BCR-free survival between groups at the end of the analysis. CONCLUSIONS: Personalised ICG-guided PLND is a promising technique to stage patients with intermediate- and high-risk PCa properly. It has shown a lower complication rate than ePLND with similar oncological outcomes at short-term follow-up.

Systems Age: A single blood methylation test to quantify aging heterogeneity across 11 physiological systems.

Individuals, organs, tissues, and cells age in diverse ways throughout the lifespan. Epigenetic clocks attempt to quantify differential aging between individuals, but they typically summarize aging as a single measure, ignoring within-person heterogeneity. Our aim was to develop novel systems-based methylation clocks that, when assessed in blood, capture aging in distinct physiological systems. We combined supervised and unsupervised machine learning methods to link DNA methylation, system-specific clinical chemistry and functional measures, and mortality risk. This yielded a panel of 11 system-specific scores- Heart, Lung, Kidney, Liver, Brain, Immune, Inflammatory, Blood, Musculoskeletal, Hormone, and Metabolic. Each system score predicted a wide variety of outcomes, aging phenotypes, and conditions specific to the respective system, and often did so more strongly than existing epigenetic clocks that report single global measures. We also combined the system scores into a composite Systems Age clock that is predictive of aging across physiological systems in an unbiased manner. Finally, we showed that the system scores clustered individuals into unique aging subtypes that had different patterns of age-related disease and decline. Overall, our biological systems based epigenetic framework captures aging in multiple physiological systems using a single blood draw and assay and may inform the development of more personalized clinical approaches for improving age-related quality of life.

Subclinical Vascular Composites Predict Clinical Cardiovascular Disease, Stroke, and Dementia: The Multi-Ethnic Study of Atherosclerosis (MESA).

Background: Subclinical cardiovascular disease (CVD) measures may reflect biological pathways that contribute to increased risk for coronary heart disease (CHD) events, stroke, and dementia beyond conventional risk scores. Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) followed 6,814 participants (45-84 years of age) from baseline in 2000-2002 to 2018 over 6 clinical examinations and annual follow-up interviews. MESA baseline subclinical CVD procedures included: seated and supine blood pressure, coronary calcium scan, radial artery tonometry, and carotid ultrasound. Baseline subclinical CVD measures were transformed into z-scores before factor analysis to derive composite factor scores. Time to clinical event for all CVD, CHD, stroke and ICD code-based dementia events were modeled using Cox proportional hazards models reported as area under the curve (AUC) with 95% Confidence Intervals (95%CI) at 10 and 15 years of follow-up. All models included all factor scores together and adjustment for conventional risk scores for global CVD, stroke, and dementia. Results: After factor selection, 24 subclinical measures aggregated into four distinct factors representing: blood pressure, arteriosclerosis, atherosclerosis, and cardiac factors. Each factor significantly predicted time to CVD events and dementia at 10 and 15 years independent of each other and conventional risk scores. Subclinical vascular composites of arteriosclerosis and atherosclerosis best predicted time to clinical events of CVD, CHD, stroke, and dementia. These results were consistent across sex and racial and ethnic groups. Conclusions: Subclinical vascular composites of arteriosclerosis and atherosclerosis may be useful biomarkers to inform the vascular pathways contributing to events of CVD, CHD, stroke, and dementia.

Associations of Accelerometer-Measured Physical Activity and Sedentary Time With All-Cause Mortality by Genetic Predisposition for Longevity.

The goal of this study was to examine associations between accelerometer-measured physical activity (PA) and sedentary time (ST) with mortality by a genetic risk score (GRS) for longevity. Among 5,446 women, (mean [SD]: age, 78.2 [6.6] years), 1,022 deaths were observed during 33,350 person-years of follow-up. Using multivariable Cox proportional hazards models, higher light PA and moderate to vigorous PA were associated with lower mortality across all GRS for longevity categories (low/medium/high; all ptrend < .001). Higher ST was associated with higher mortality (ptrend across all GRS categories < .001). Interaction tests for PA and ST with the GRS were not statistically significant. Findings support the importance of higher PA and lower ST for reducing mortality risk in older women, regardless of genetic predisposition for longevity.

The relationship between optimism, MCI, and dementia among postmenopausal women.

OBJECTIVES: The relationship between optimism and cognitive functioning is not fully understood. We examined the association of optimism with risk of mild cognitive impairment (MCI) and dementia in the Women's Health Initiative Memory Study (WHIMS). METHODS: Optimism was measured by the Life Orientation Test-Revised (LOT-R) total score, and optimism and pessimism subscales. A panel of experts adjudicated cognitive endpoints based on annual cognitive assessments. We used cox proportional hazard regression models to examine the association of LOT-R total score and optimism and pessimism sub-scores with MCI/dementia. We also examined the relationship between vascular disease, LOT-R total score, optimism and pessimism, and cognition. RESULTS: Mean age was 70.5 (SD = 3.9) years. The sample (N = 7249) was 87% white, and 29.8% of participants had < 12 years of education. Total LOT-R score (HR = 0.96, 95% CI: 0.94, 0.98, p < 0.001) was associated with lower risk of combined MCI or dementia. More pessimism (HR = 1.08, 95% CI: 1.05, 1.11, p < 0.0001) was associated with higher risk of MCI or dementia after adjustment for ethnicity, education, vascular disease, and depression. No significant relationships emerged from the optimism subscale. CONCLUSION: These data suggest that less pessimism, but not more optimism, was associated with a lower risk of MCI and dementia.