Hospitalized COVID-19 patients tend to be older and frequently have hypertension, diabetes or coronary heart disease (CHD), but whether these co-morbidities are true risk factors (i.e. more common than in the general older population) is unclear. We estimated associations between pre-existing diagnoses and hospitalized COVID-19 alone or with mortality, in a large community cohort. UK Biobank (England) participants with baseline assessment 2006 to 2010, followed in hospital discharge records to 2017 and death records to 2020. Demographic and pre-existing common diagnoses association tested with hospitalized laboratory confirmed COVID-19 (16^th March to 26^th April 2020), alone or with mortality, in logistic models. Of 269,070 participants aged 65+, 507 (0.2%) became COVID-19 hospital inpatients, of which 141 (27.8%) died. Common co-morbidities in hospitalized inpatients were hypertension (59.6%), history of fall or fragility fractures (29.4%), coronary heart disease (CHD, 21.5%), type 2 diabetes (type 2, 19. 9%) and asthma (17.6%). However, in models adjusted for comorbidities, age-group, sex, ethnicity and education, pre-existing diagnoses of dementia, type 2 diabetes, COPD, pneumonia, depression, atrial fibrillation and hypertension emerged as independent risk factors for COVID-19 hospitalization, the first five remaining statistically significant for related mortality. Chronic Kidney Disease and asthma were risk factors for COVID-19 hospitalization in women but not men. There are specific high risk pre-existing co-morbidities for COVID-19 hospitalization and related deaths in community based older men and women. These results do not support simple age-based targeting of the older population to prevent severe COVID-19 infections.

Chia-Ling Kuo, PhD, Luke C Pilling, PhD, Janice L Atkins, PhD, Jane A H Masoli, MBChB, João Delgado, PhD, George A Kuchel, MD, David Melzer, MBBCh PhD; APOE e4

Biological age measures outperform chronological age in predicting various aging outcomes, yet little is known regarding genetic predisposition. We performed genome‐wide association scans of two age‐adjusted biological age measures (PhenoAgeAcceleration and BioAgeAcceleration), estimated from clinical biochemistry markers (Levine et al., 2018; Levine, 2013) in European‐descent participants from UK Biobank. The strongest signals were found in the APOE gene, tagged by the two major protein‐coding SNPs, PhenoAgeAccel—rs429358 (APOE e4 determinant) (p = 1.50 × 10⁻⁷²); BioAgeAccel—rs7412 (APOE e2 determinant) (p = 3.16 × 10⁻⁶⁰). Interestingly, we observed inverse APOE e2 and e4 associations and unique pathway enrichments when comparing the two biological age measures. Genes associated with BioAgeAccel were enriched in lipid related pathways, while genes associated with PhenoAgeAccel showed enrichment for immune system, cell function, and carbohydrate homeostasis pathways, suggesting the two measures capture different aging domains. Our study reaffirms that aging patterns are heterogeneous across individuals, and the manner in which a person ages may be partly attributed to genetic predisposition.

Matching on demographic variables is commonly used in case–control studies to adjust for confounding at the design stage. There is a presumption that matched data need to be analyzed by matched methods. Conditional logistic regression has become a standard for matched case–control data to tackle the sparse data problem. The sparse data problem, however, may not be a concern for loose-matching data when the matching between cases and controls is not unique, and one case can be matched to other controls without substantially changing the association. Data matched on a few demographic variables are clearly loose-matching data, and we hypothesize that unconditional logistic regression is a proper method to perform. To address the hypothesis, we compare unconditional and conditional logistic regression models by precision in estimates and hypothesis testing using simulated matched case–control data. Our results support our hypothesis; however, the unconditional model is not as robust as the conditional model to the matching distortion that the matching process not only makes cases and controls similar for matching variables but also for the exposure status. When the study design involves other complex features or the computational burden is high, matching in loose-matching data can be ignored for negligible loss in testing and estimation if the distributions of matching variables are not extremely different between cases and controls.

Inherited genetic variation influencing leukocyte telomere length provides a natural experiment for testing associations with health outcomes, more robust to confounding and reverse causation than observational studies. We tested associations between genetically determined telomere length and aging‐related health outcomes in a large European ancestry older cohort. Data were from n = 379,758 UK Biobank participants aged 40–70, followed up for mean of 7.5 years (n = 261,837 participants aged 60 and older by end of follow‐up). Thirteen variants strongly associated with longer telomere length in peripheral white blood cells were analyzed using Mendelian randomization methods with Egger plots to assess pleiotropy. Variants in TERC, TERT, NAF1, OBFC1, and RTEL1 were included, and estimates were per 250 base pairs increase in telomere length, approximately equivalent to the average change over a decade in the general white population. We highlighted associations with false discovery rate‐adjusted p‐values smaller than .05. Genetically determined longer telomere length was associated with lowered risk of coronary heart disease (CHD; OR = 0.95, 95% CI: 0.92–0.98) but raised risk of cancer (OR = 1.11, 95% CI: 1.06–1.16). Little evidence for associations were found with parental lifespan, centenarian status of parents, cognitive function, grip strength, sarcopenia, or falls. The results for those aged 60 and older were similar in younger or all participants. Genetically determined telomere length was associated with increased risk of cancer and reduced risk of CHD but little change in other age‐related health outcomes. Telomere lengthening may offer little gain in later‐life health status and face increasing cancer risks.

We previously reported that the ApoE e4e4 genotype was associated with COVID-19 test positivity (odds ratio [OR] = 2.31, 95% CI: 1.65–3.24, p = 1.19 × 10⁻⁶) ( 1) in the UK Biobank (UKB) cohort, during the epidemic peak in England, from March 16 to April 26, 2020 ( 2). With more COVID-19 test results (March 16 to May 31, 2020) and mortality data (to March 31, 2020, with incomplete data for April 2020) linked to UKB, we reevaluated the ApoE e4 allele association with COVID-19 test positivity, and with all-cause mortality following test-confirmed COVID-19.