The search for reliable indicators of biological age, rather than chronological age, has been ongoing for over three decades, and until recently, largely without success. Advances in the fields of molecular biology have increased the variety of potential candidate biomarkers that may be considered as biological age predictors. In this review, we summarize current state-of-the-art findings considering six potential types of biological age predictors: epigenetic clocks, telomere length, transcriptomic predictors, proteomic predictors, metabolomics-based predictors, and composite biomarker predictors. Promising developments consider multiple combinations of these various types of predictors, which may shed light on the aging process and provide further understanding of what contributes to healthy aging. Thus far, the most promising, new biological age predictor is the epigenetic clock; however its true value as a biomarker of aging requires longitudinal confirmation.

Biological age measurements (BAs) assess aging-related physiological change and predict health risks among individuals of the same chronological age (CA). Multiple BAs have been proposed and are well studied individually but not jointly. We included 845 individuals and 3973 repeated measurements from a Swedish population-based cohort and examined longitudinal trajectories, correlations, and mortality associations of nine BAs across 20 years follow-up. We found the longitudinal growth of functional BAs accelerated around age 70; average levels of BA curves differed by sex across the age span (50–90 years). All BAs were correlated to varying degrees; correlations were mostly explained by CA. Individually, all BAs except for telomere length were associated with mortality risk independently of CA. The largest effects were seen for methylation age estimators (GrimAge) and the frailty index (FI). In joint models, two methylation age estimators (Horvath and GrimAge) and FI remained predictive, suggesting they are complementary in predicting mortality.

Objectives To analyze whether frailty and comorbidities are associated with in-hospital mortality and discharge to home in older adults hospitalized for coronavirus disease 2019 (COVID-19). Design Single-center observational study. Setting and Participants Patients admitted to geriatric care in a large hospital in Sweden between March 1 and June 11, 2020; 250 were treated for COVID-19 and 717 for other diagnoses. Methods COVID-19 diagnosis was clinically confirmed by positive reverse transcription polymerase chain reaction test or, if negative, by other methods. Patient data were extracted from electronic medical records, which included Clinical Frailty Scale (CFS), and were further used for assessments of the Hospital Frailty Risk Score (HFRS) and the Charlson Comorbidity Index (CCI). In-hospital mortality and home discharge were followed up for up to 25 and 28 days, respectively. Multivariate Cox regression models adjusted for age and sex were used. Results Among the patients with COVID-19, in-hospital mortality rate was 24% and home discharge rate was 44%. Higher age was associated with in-hospital mortality (hazard ratio [HR] 1.05 per each year, 95% confidence interval [CI] 1.01‒1.08) and lower probability of home discharge (HR 0.97, 95% CI 0.95‒0.99). CFS (>5) and CCI, but not HFRS, were predictive of in-hospital mortality (HR 1.93, 95% CI 1.02‒3.65 and HR 1.27, 95% CI 1.02‒1.58, respectively). Patients with CFS >5 had a lower probability of being discharged home (HR 0.38, 95% CI 0.25‒0.58). CCI and HFRS were not associated with home discharge. In general, effects were more pronounced in men. Acute kidney injury was associated with in-hospital mortality and hypertension with discharge to home. Other comorbidities (diabetes, cardiovascular disease, lung diseases, chronic kidney disease and dementia) were not associated with either outcome. Conclusions and Implications Of all geriatric patients with COVID-19, 3 out of 4 survived during the study period. Our results indicate that in addition to age, the level of frailty is a useful predictor of short-term COVID-19 outcomes in geriatric patients.

Objective: To validate new mitochondrial myopathy serum biomarkers for diagnostic use. Methods:We analyzed serum FGF21 (S-FGF21) and GDF15 from patients with (1) mitochondrial diseases and (2) nonmitochondrial disorders partially overlapping with mitochondrial disorder phenotypes. We (3) did a meta-analysis of S-FGF21 in mitochondrial disease and (4) analyzed S-Fgf21 and skeletal muscle Fgf21 expression in 6 mouse models with different musclemanifesting mitochondrial dysfunctions.Results: We report that S-FGF21 consistently increases in primary mitochondrial myopathy, especially in patients with mitochondrial translation defects or mitochondrial DNA (mtDNA) deletions (675 and 347 pg/mL, respectively; controls: 66 pg/mL, p , 0.0001 for both). This is corroborated in mice (mtDNA deletions 1,163 vs 379 pg/mL, p , 0.0001). However, patients and mice with structural respiratory chain subunit or assembly factor defects showed low induction (human 335 pg/mL, p , 0.05; mice 335 pg/mL, not significant). Overall specificities of FGF21 and GDF15 to find patients with mitochondrial myopathy were 89.3% vs 86.4%, and sensitivities 67.3% and 76.0%, respectively. However, GDF15 was increased also in a wide range of nonmitochondrial conditions.Conclusions: S-FGF21 is a specific biomarker for muscle-manifesting defects of mitochondrial translation, including mitochondrial transfer-RNA mutations and primary and secondary mtDNA deletions, the most common causes of mitochondrial disease. However, normal S-FGF21 does not exclude structural respiratory chain complex or assembly factor defects, important to acknowledge in diagnostics. Classification of evidence:This study provides Class III evidence that elevated S-FGF21 accurately distinguishes patients with mitochondrial myopathies from patients with other conditions, and FGF21 and GDF15 mitochondrial myopathy from other myopathies. Neurology ® 2016;87:2290-2299 GLOSSARY ALS 5 amyotrophic lateral sclerosis; CI 5 confidence interval; CK 5 creatine kinase; FGF21 5 fibroblast growth factor 21; GDF15 5 growth and differentiation factor 15; mCRC 5 metastasized colorectal cancer; MM 5 mitochondrial myopathy; mtDNA 5 mitochondrial DNA; PBC 5 primary biliary cirrhosis; PSC 5 primary sclerosing cholangitis; RC 5 respiratory chain; S-FGF21 5 serum FGF21; tRNA 5 transfer RNA.Mitochondrial diseases are the most common form of inherited metabolic disorders. The high variability in clinical manifestation, heterogeneity of genetic causes with .150 known disease genes, 1 and scarcity of sensitive and specific biomarkers make their diagnosis challenging. Our original multicenter analysis identified fibroblast growth factor 21 (FGF21) induction in *These authors contributed equally to this work.

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