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PurposeLong COVID-19 syndrome occurs in 10-20 % of people after a confirmed/probable SARS-COV-2 infection; new symptoms begin within three months of COVID-19 diagnosis and last > 8 weeks. Little is known about risk factors for long COVID, particularly in older people who are at greater risk of COVID complications.MethodsData are from Women's Health Initiative (WHI) postmenopausal women who completed COVID surveys that included questions on whether they had ever been diagnosed with COVID and length and nature of symptoms. Long COVID was classified using standard consensus criteria. Using WHI demographic and health data collected at study enrollment (1993-98) through the present day, machine learning identified the top 20 risk factors for long COVID. These variables were tested in logistic regression models.ResultsOf n = 37,280 survey respondents, 1237 (mean age = 83 years) reported a positive COVID-19 test and 425 (30 %) reported long COVID. Symptoms included an array of neurological, cardio-pulmonary, musculoskeletal, and general fatigue, and malaise symptoms. Long COVID risk factors included weight loss, physical and mobility limitations, and specific heath conditions (e.g., history of heart valve procedure, rheumatoid arthritis).ConclusionsKnowledge of risk factors for long COVID may be the first step in understanding the etiology of this complex disease.

Sex and gender-biological and social constructs-significantly impact the prevalence of protective and risk factors, influencing the burden of Alzheimer's disease (AD; amyloid beta and tau) and other pathologies (e.g., cerebrovascular disease) which ultimately shape cognitive trajectories. Understanding the interplay of these factors is central to understanding resilience and resistance mechanisms explaining maintained cognitive function and reduced pathology accumulation in aging and AD. In this narrative review, the ADDRESS! Special Interest Group (Alzheimer's Association) adopted a multidisciplinary approach to provide the foundations and recommendations for future research into sex- and gender-specific drivers of resilience, including a sex/gender-oriented review of risk factors, genetics, AD and non-AD pathologies, brain structure and function, and animal research. We urge the field to adopt a sex/gender-aware approach to resilience to advance our understanding of the intricate interplay of biological and social determinants and consider sex/gender-specific resilience throughout disease stages. HIGHLIGHTS: Sex differences in resilience to cognitive decline vary by age and cognitive status. Initial evidence supports sex-specific distinctions in brain pathology. Findings suggest sex differences in the impact of pathology on cognition. There is a sex-specific change in resilience in the transition to clinical stages. Gender and sex factors warrant study: modifiable, immune, inflammatory, and vascular.

BACKGROUND & AIMS: Systematic reviews, meta-analyses and Mendelian randomization studies suggest that cardiometabolic diseases may be associated with COVID-19 risk and prognosis, with evidence implicating insulin resistance (IR) as a common biological mechanism. As driving factors for IR, we examined body mass index (BMI) and waist circumference (WC) among postmenopausal women in association with COVID-19 outcomes (positivity and hospitalization), and the role of glucose homeostasis as a mediator of this relationship. METHODS: Associations of BMI and WC at baseline (1993-1998) with COVID-19 outcomes collected at Survey 1 (June-December, 2020) and/or Survey 2 (September-December, 2021) were evaluated among 42,770 Womens Health Initiative (WHI) participants (baseline age: 59.36 years) of whom 16,526 self-reported having taken ≥1 COVID-19 test, with 1242 reporting ≥1 positive COVID-19 test and 362 reporting ≥1 COVID-19 hospitalization. We applied logistic regression and causal mediation analyses to sub-samples with available fasting biomarkers of glucose homeostasis (glucose, insulin, Homeostatic Model Assessment for Insulin Resistance, Homeostasis Model Assessment for β-cell function, Quantitative Insulin-sensitivity Check Index, Triglyceride-Glucose index (TyG)) at baseline, whereby 57 of 759 reported COVID-19 test positivity and 23 of 1896 reported COVID-19 hospitalization. RESULTS: In fully adjusted models, higher BMI, WC and TyG were associated with COVID-19 test positivity and hospitalization. Glucose concentrations mediated associations of BMI and WC with COVID-19 positivity, whereas TyG mediated BMI and WCs associations with COVID-19 hospitalization. CONCLUSIONS: Obesity and central obesity markers collected an average of 24 years prior were associated with COVID-19 outcomes among postmenopausal women. Glucose concentration and TyG partly mediated these associations.

Biologic aging reflects the genetic, molecular, and cellular changes underlying the development of morbidity and mortality with advancing chronological age. As several potential mechanisms have been identified, there is a growing interest in developing robust measures of biologic age that can better reflect the underlying biology of aging and predict age-related outcomes. To support this endeavor, the Research Centers Collaborative Network (RCCN) conducted a workshop in January 2022 to discuss emerging concepts in the field and identify opportunities to move the science forward. This paper presents workshop proceedings and summarizes the identified research needs, priorities, and recommendations for measuring biologic age. The highest priorities identified were the need for more robust measures, longitudinal studies, multidisciplinary collaborations, and translational approaches.

INTRODUCTION: Identifying people at high risk of Alzheimer's disease (AD) dementia allows for timely intervention, which, if successful, will result in preventing or delaying the onset of the disease. METHODS: Utilizing data from the Chicago Health and Aging Project (CHAP; n = 2130), we externally evaluated four risk‐prediction models for AD dementia, including Cardiovascular Risk Factors, Aging, and Dementia (CAIDE), Australian National University Alzheimer's Disease Risk Index (ANU‐ADRI), Brief Dementia Screening Indicator (BDSI), and Dementia Risk Score (DRS), in Black or African American and White adults. RESULTS: BDSI had the highest discriminate abilities for AD dementia (c‐statistics of 0.79 in Black and 0.77 in White adults), followed by ANU‐ADRI, within the age range and follow‐up period of the original development cohort. CAIDE had the lowest discriminating power (c‐statistic ≤0.55). With increasing follow‐up periods (i.e., 10–15 years), the discrimination abilities for all models declined. DISCUSSION: Because of racial disparities in AD dementia and longer preclinical and prodromal stages of disease development, race‐specific models are needed to predict AD risk over 10 years. Highlights: Utilizing risk‐prediction models to identify individuals at higher risk of Alzheimer's disease (AD) dementia could benefit clinicians, patients, and policymakers. Clinicians could enroll high‐risk individuals in clinical trials to test new risk‐modifiable treatments or initiate lifestyle modifications, which, if successful, would slow cognitive decline and delay the onset of the disease.Current risk‐prediction models had good discriminative power during the first 6 years of follow‐up but decreased with longer follow‐up time.Acknowledging the longer preclinical phase of AD dementia development and racial differences in dementia risk, there is a need to develop race‐specific risk‐prediction models that can predict 10 or 20 years of risk for AD and related dementias. [ABSTRACT FROM AUTHOR]

INTRODUCTION: It is unclear whether inflammation, that is, high interleukin‐6 (IL‐6) levels, and genetic risk, that is, apolipoprotein E (APOE) ε4 allele, have a compounding effect on cognitive decline (CD). METHODS: We analyzed a subset of participants from the longitudinal cohort study, Chicago Health and Aging Project, comprising 1120 biracial community‐dwelling older adults (60% Black and 62% women), and mean follow‐up = 6.4 years. We ran adjusted mixed‐effects models on2 longitudinal CD. RESULTS: In APOE ε4 carriers, higher serum IL‐6 was not associated with the rate of CD (β = –0.0091 [standard deviation (SD) = 0.0165, p = 0.5800]). Conversely, in non‐ε4 carriers, compared to the lower tertile, those with the upper tertile of serum IL‐6 levels experienced significantly accelerated CD (β = –0.0257 [SD = 0.0084, p = 0.0023]). DISCUSSION: Even without the largest genetic risk factor for late‐onset Alzheimer's disease/Alzheimer's disease and related dementias (AD/ADRD), elevated serum IL‐6 still accelerate the rate of CD in non‐APOE ε4 carriers. Hence, interventions ameliorating inflammation may prevent AD/ADRD. Highlights: Interleukin‐6 (IL‐6) and the apolipoprotein E (APOE) ε4 allele have been separately associated with an increased risk for cognitive decline, but their interaction remains unclear.In ε4 carriers, IL‐6 was not associated with cognitive decline. However, even without the biggest genetic risk factor for Alzheimer's disease (AD), that is, APOE ε4, elevated serum IL‐6 still could confer accelerated rate of cognitive decline, with a detrimental effect half of that imposed by APOE ε4 alone.We found no racial differences in these associations.These findings contribute complementary evidence on non–APOE ε4‐dependent and non‐AD biological pathways through which cognitive decline can still be accelerated in non‐APOE ε4 carriers and highlight a specific subgroup of older adults who are at a higher risk of AD and thus may benefit from anti‐inflammatory interventions. [ABSTRACT FROM AUTHOR]

University-based retirement communities (UBRCs) are a relatively recent addition to housing options for older adults. The case example of a new UBRC, Mirabella at Arizona State University (ASU), is presented within the context of Age-Friendly University (AFU) principles and New American University design aspirations. We provide an overview of the planning process, describe initial collaborations between Mirabella and research faculty, and outline areas of overlap and distinction between Mirabella's approach and other UBRCs, AFU principles, and the design aspirations of the New American University model. Empirical investigations are needed to identify key characteristics of UBRCs that facilitate university integration and how those characteristics impact individual, community, and university level outcomes. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Patients with Alzheimer's disease present with difficulty in lexical retrieval and reversal of the concreteness effect in nouns. Little is known about the phenomena before the onset of symptoms. We anticipate early linguistic signs in the speech of people who suffer from amnestic mild cognitive impairment (MCI). Here, we report the results of a corpus‐linguistic approach to the early detection of cognitive impairment. METHODS: One hundred forty‐eight English‐speaking Singaporeans provided natural speech data, on topics of their choice; 74 were diagnosed with single‐domain MCI (38 amnestic, 36 non‐amnestic), 74 cognitively healthy. The recordings yield 267,310 words, which are tagged for parts of speech. We calculate the per‐minute word counts and concreteness scores of all tagged words, nouns, and verbs in the dataset. RESULTS: Compared to controls, subjects with amnestic MCI produce fewer but more abstract nouns. Verbs are not affected. DISCUSSION: Slower retrieval of nouns and the reversal of the concreteness effect in nouns are manifested in natural speech and can be detected early through corpus‐based analysis. Highlights: Reversal of the concreteness effect is manifested in patients with Alzheimer's disease (AD) and semantic dementia.The paper reports a corpus‐based analysis of natural speech by people with amnestic and non‐amnestic mild cognitive impairment (MCI) and cognitively healthy controls.People with amnestic MCI produce fewer and more abstract nouns than people with non‐amnestic MCI and healthy controls. Verbs appear to be unaffected.The imageability problem can be detected in natural everyday speech by people with amnestic MCI, which carries a higher risk of conversion to AD. [ABSTRACT FROM AUTHOR]

Background Health-related quality of life (HRQoL) measures are predictors of adverse health outcomes in older adults. Studies have demonstrated cross-sectional associations between HRQoL measures and blood-based biochemical markers. Acylcarnitines (ACs) are a class of metabolites generated in the mitochondria and are predictive of multiple geriatric syndromes. Changes in ACs reflect alterations in central carbon metabolic pathways. However, the prospective relationship between plasma ACs and declining HRQoL has not been examined. This study aimed to investigate both cross-sectional and longitudinal associations of baseline ACs with baseline and declining EuroQol-5 Dimension/EuroQol Visual Analogue Scale (EQ-5D/EQ-VAS) in community-dwelling older adults. Methods One hundred and twenty community-dwelling older adults with EQ-5D/EQ-VAS measurements at baseline and follow-up were included. We quantified ACs at baseline using targeted plasma metabolomics profiling. Multivariate regressions were performed to examine cross-sectional and longitudinal associations between the measures. Results Cross-sectionally, ACs showed no significant associations with either EQ-5D index or EQ-VAS scores. Longitudinally, multiple baseline short-chain ACs were significantly and inversely associated with declining EQ-5D index score, explaining up to 8.5% of variance in the decline. Conclusions Within a cohort of community-dwelling older adults who had high HRQoL at baseline, we showed that higher levels of short-chain ACs are longitudinally associated with declining HRQoL. These findings reveal a novel association between central carbon metabolic pathways and declining HRQoL. Notably, dysregulation in mitochondrial central carbon metabolism could be detected prior to clinically important decline in HRQoL, providing the first evidence of objective biomarkers as novel predictors to monitor HRQoL in nonpharmacological interventions and epidemiology. [ABSTRACT FROM AUTHOR]

Background Loneliness precedes the onset of cognitive impairment (CI) in older adults. Although the mechanisms through which loneliness "gets under the skin" to influence the risk of developing CI have been conceptually proposed, they are rarely empirically examined. The Evolutionary Theory of Loneliness posits that loneliness as a stressor could cause dysregulations in multiple physiological systems. The current study investigated whether inflammatory, cardiovascular, and kidney biomarkers mediate the longitudinal association between loneliness and CI. Methods Cross-lagged panel models were used to examine the hypothesized relationships, using 2006, 2010, and 2014 waves of data from the Health and Retirement Study (N = 7,037). Loneliness was measured with the 3-item UCLA loneliness scale. CI was assessed with the modified telephone interview for cognitive status. Biomarkers included HbA1C, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, C-reactive protein, and Cystatin C. Using a stepwise model-building approach, first, the model included only loneliness, CI, and biomarker variables; then, sociodemographic covariates were added; lastly, health status were controlled for. Results In unadjusted and partially adjusted models, loneliness was associated with higher odds of worse cognitive status in an 8-year follow-up. Only HbA1C mediated the longitudinal association between loneliness and CI. However, after further controlling for health status, all associations became nonsignificant. Conclusions Examining a large number of participants and linking a limited number of biological markers with cognition and loneliness longitudinally, our empirical data did not support theoretical propositions, highlighting the critical importance of controlling for confounders in future studies examining longitudinal mediational relationships underlying loneliness and CI. [ABSTRACT FROM AUTHOR]