Deciphering the genetic and epidemiological landscape of mitochondrial DNA abundance

Acknowledgements: The computations and data handling were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at UPPMAX, Uppsala University, partially funded by the Swedish Research Council through grant agreement no. 2018-05973. This research has been conducted using the UK Biobank Resource under Application Number 22224. Funding: Open Access funding provided by Karolinska Institute. Open Access funding provided by Karolinska Institute. This work was financed by the Swedish Research Council (Grant 2018-02547, 2015-03255, 2019-01272, 2018-02077), the Swedish Cancer Society (Grants CAN 2016/684), the Stockholm County Council (Grant no. 20170088), the Karolinska Institutet’s Research Foundation (Grant 2018-02146), Karolinska Institutet’s Strategic Research Program in Epidemiology, King Gustaf V:s and Queen Victoria's Foundation of Freemasons, and the Åke Wibergs Foundation (M19-0294). FG was a Leopoldina Postdoctoral Fellow (Grant no. LPDS 2018-06) funded by the Academy of Sciences Leopoldina. Correction to: Deciphering the genetic and epidemiological landscape of mitochondrial DNA abundance (Human Genetics, (2020), 10.1007/s00439-020-02249-w) The data were exclusively retrieved from the UK Biobank and can be accessed upon request from the UK Biobank. The mitochondrial DNA abundance as computed in this manuscript will be reported back to the UK Biobank upon publication. The scripts to compute the weights and the weighted mtDNA abundance in the UKB dataset will be published at https://github.com/GrassmannLab/MT_UKB.Peer reviewedPublisher PD

Dementia and psychotropic medications are associated with significantly higher mortality in geriatric patients hospitalized with COVID-19 : data from the StockholmGeroCovid project

Background: Dementia and psychotropic medications are discussed as risk factors for severe/lethal outcome of the coronavirus disease 2019 (COVID-19). We aimed to explore the associations between the presence of dementia and medication use with mortality in the hospitalized and discharged patients who suffered from COVID-19. Methods: We conducted an open-cohort observational study based on electronic patient records from nine geriatric care clinics in the larger Stockholm area, Sweden, between February 28, 2020, and November 22, 2021. In total, we identified 5122 hospitalized patients diagnosed with COVID-19, out of which 762 (14.9%) patients had concurrent dementia and 4360 (85.1%) were dementia-free. Patients’ age, sex, baseline oxygen saturation, comorbidities, and medication prescription (cardiovascular and psychotropic medication) were registered at admission. The hazard ratios (HRs) with 95% confidence intervals (CIs) of in-hospital, 30-day, 90-day, 365-day post-discharge, and overall mortal- ity during the follow-up were obtained. Then, the associations of dementia and medication use with mortality were determined using proportional hazards regression with time since entry as a time scale. Results: After adjustment, dementia was independently associated with 68% higher in-hospital mortality among COVID-19 patients compared to patients who were dementia-free at admission [HRs (95% CI) 1.68 (1.37–2.06)]. The increase was consistent post-discharge, and the overall mortality of dementia patients was increased by 59% [1.59 (1.40–1.81)]. In addition, the prescription of antipsychotic medication at hospital admission was associated with a 70% higher total mortality risk [1.70 (1.47–1.97)]. Conclusions: The clinical co-occurence of dementia and COVID-19 increases the short- and long-term risk of death, and the antipsychotics seem to further the risk increase. Our results may help identify high-risk patients in need of more specialized care when infected with COVID-19.Swedish Research Council (dnr: 2020-06101 WISER, 2021-013167, 2020-05805)National Institute for Neurological Research, Programme EXCELES (Project No. LX22NPO5107)European Union, Next Generation EUAlzheimerfondenKarolinska InstitutetPublishe

Can frailty scores predict the incidence of cancer? : Results from two large population-based studies

While chronological age is the single biggest risk factor for cancer, it is less clear whether frailty, an age-related state of physiological decline, may also predict cancer incidence. We assessed the associations of frailty index (FI) and frailty phenotype (FP) scores with the incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, melanoma) in 453,144 UK Biobank (UKB) and 36,888 Screening Across the Lifespan Twin study (SALT) participants, who aged 38–73 years and had no cancer diagnosis at baseline. During a median follow-up of 10.9 and 10.7 years, 53,049 (11.7%) and 4,362 (11.8%) incident cancers were documented in UKB and SALT, respectively. Using multivariable-adjusted Cox models, we found a higher risk of any cancer in frail vs. non-frail UKB participants, when defined by both FI (hazard ratio [HR] = 1.22; 95% confidence interval [CI] = 1.17–1.28) and FP (HR = 1.16; 95% CI = 1.11–1.21). The FI in SALT similarly predicted risk of any cancer (HR = 1.31; 95% CI = 1.15–1.49). Moreover, frailty was predictive of lung cancer in UKB, although this association was not observed in SALT. Adding frailty scores to models including age, sex, and traditional cancer risk factors resulted in little improvement in C-statistics for most cancers. In a within-twin-pair analysis in SALT, the association between FI and any cancer was attenuated within monozygotic but not dizygotic twins, indicating that it may partly be explained by genetic factors. Our findings suggest that frailty scores are associated with the incidence of any cancer and lung cancer, although their clinical utility for predicting cancers may be limited.publishedVersionPeer reviewe

The association between mitochondrial DNA abundance and stroke : A combination of multivariable-adjusted survival and Mendelian randomization analyses

Acknowledgements The authors are grateful to the UK Biobank for allowing us the use of their data. The analyses done in UK Biobank were done under project number 56340. Furthermore, the authors acknowledge the participants and investigators of the MEGASTROKE consortium and the FinnGen Biobank who contributed to the summary statistics data which are made available for further studies. Financial support This work was supported by the VELUX Stiftung [grant number 1156] to DvH and RN, and JL was supported by the China Scholarship Counsel [No.201808500155]. RN was supported by an innovation grant from the Dutch Heart Foundation [grant number 2019T103 to R.N.]. Parts of this work were funded by the Åke Wibergs Foundation (grant number M19-0294 to F.G).Peer reviewedPublisher PD

Is Frailty Different in Younger Adults Compared to Old? Prevalence, Characteristics, and Risk Factors of Early-Life and Late-Life Frailty in Samples from Sweden and UK

Introduction: Although frailty is commonly considered as a syndrome of old individuals, recent studies show that it can affect younger adults, too. Whether and how frailty differs in younger adults compared to old is however unknown. To this end, we analyzed the prevalence, characteristics, and risk factors of early-life (aged <65) and late-life (aged ≥65) frailty. Methods: We analyzed individuals in the UK Biobank (N = 405,123) and Swedish Screening Across the Lifespan Twin (SALT; N = 43,641) study. Frailty index (FI) scores ≥0.21 were used to demarcate frailty. Characteristics of early-life versus late-life frailty were analyzed by collating the FI items (deficits) into domains and comparing the domain scores between younger and older frail individuals. Logistic regression was used to assess the risk factors of frailty. Results: The pooled prevalence rates of frailty were 10.3% (95% confidence interval [CI]: 2.7-32.7), 14.4% (95% CI: 4.5-37.2), 19.2% (95% CI: 2.5-68.5) in individuals aged ≤55, 55-64, 65-74, respectively. Younger frail adults (aged <65) had higher scores in immunological, mental wellbeing, and pain-related domains, whereas older frail adults (aged ≥65) had higher scores in cardiometabolic, cancer, musculoskeletal, and sensory-related domains. Higher age, female sex, smoking, lower alcohol consumption, lower education, obesity, overweight, low income, and maternal smoking were similarly associated with the risk of early-life and late-life frailty. Conclusion: Frailty is prevalent also in younger age groups (aged <65) but differs in some of its characteristics from the old. The risk factors of frailty are nevertheless largely similar for early-life and late-life frailty.Peer reviewe

Clinical and MRI Features of Cerebral Small-Vessel Disease in Type 1 Diabetes

OBJECTIVETo assess the prevalence of cerebral small-vessel disease (SVD) in subjects with type 1 diabetes compared with healthy control subjects and to characterize the diabetes-related factors associated with SVD.RESEARCH DESIGN AND METHODSThis substudy was cross-sectional in design and included 191 participants with type 1 diabetes and median age 40.0 years (interquartile range 33.0-45.1) and 30 healthy age- and sex-matched control subjects. All participants underwent clinical investigation and brain MRIs, assessed for cerebral SVD.RESULTSCerebral SVD was more common in participants with type 1 diabetes than in healthy control subjects: any marker 35% vs. 10% (P = 0.005), cerebral microbleeds (CMBs) 24% vs. 3.3% (P = 0.008), white matter hyperintensities 17% vs. 6.7% (P = 0.182), and lacunes 2.1% vs. 0% (P = 1.000). Presence of CMBs was independently associated with systolic blood pressure (odds ratio 1.03 [95% CI 1.00-1.05], P = 0.035).CONCLUSIONSCerebral SVD, CMBs in particular, is more common in young people with type 1 diabetes compared with healthy control subjects.Peer reviewe

Rare functional variants in the CRP and G6PC genes modify the relationship between obesity and serum C-reactive protein in white British population

Background: C-reactive protein (CRP) is a sensitive biomarker of inflammation with moderate heritability. The role of rare functional genetic variants in relation to serum CRP is understudied. We aimed to examine gene mutation burden of protein-altering (PA) and loss-of-function (LOF) variants in association with serum CRP, and to further explore the clinical relevance. Methods: We included 161,430 unrelated participants of European ancestry from the UK Biobank. Of the rare (minor allele frequency <0.1%) and functional variants, 1,776,249 PA and 266,226 LOF variants were identified. Gene-based burden tests, linear regressions, and logistic regressions were performed to identify the candidate mutations at the gene and variant levels, to estimate the potential interaction effect between the identified PA mutation and obesity, and to evaluate the relative risk of 16 CRP-associated diseases. Results: At the gene level, PA mutation burdens of the CRP (β = −0.685, p = 2.87e-28) and G6PC genes (β = 0.203, p = 1.50e-06) were associated with reduced and increased serum CRP concentration, respectively. At the variant level, seven PA alleles in the CRP gene decreased serum CRP, of which the per-allele effects were approximately three to seven times greater than that of a common variant in the same locus. The effects of obesity and central obesity on serum CRP concentration were smaller among the PA mutation carriers in the CRP (pinteraction = 0.008) and G6PC gene (pinteraction = 0.034) compared to the corresponding non-carriers. Conclusion: PA mutation burdens in the CRP and G6PC genes are strongly associated with decreased serum CRP concentrations. As serum CRP and obesity are important predictors of cardiovascular risks in clinics, our observations suggest taking rare genetic factors into consideration might improve the delivery of precision medicine.Peer reviewe

Biological aging of different blood cell types

Biological age (BA) captures detrimental age-related changes. The best-known and most-used BA indicators include DNA methylation–based epigenetic clocks and telomere length (TL). The most common biological sample material for epidemiological aging studies, whole blood, is composed of different cell types. We aimed to compare differences in BAs between blood cell types and assessed the BA indicators’ cell type-specific associations with chronological age (CA). An analysis of DNA methylation–based BA indicators, including TL, methylation level at cg16867657 in ELOVL2, as well as the Hannum, Horvath, DNAmPhenoAge, and DunedinPACE epigenetic clocks, was performed on 428 biological samples of 12 blood cell types. BA values were different in the majority of the pairwise comparisons between cell types, as well as in comparison to whole blood (p < 0.05). DNAmPhenoAge showed the largest cell type differences, up to 44.5 years and DNA methylation-based TL showed the lowest differences. T cells generally had the "youngest" BA values, with differences across subsets, whereas monocytes had the "oldest" values. All BA indicators, except DunedinPACE, strongly correlated with CA within a cell type. Some differences such as DNAmPhenoAge-difference between naïve CD4 + T cells and monocytes were constant regardless of the blood donor's CA (range 20–80 years), while for DunedinPACE they were not. In conclusion, DNA methylation–based indicators of BA exhibit cell type–specific characteristics. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and underscore the importance of considering cell composition when utilizing them as indicators for the success of aging interventions.Peer reviewe

Temporal Dynamics of Epigenetic Aging and Frailty From Midlife to Old Age

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Genetic and environmental influences on longitudinal frailty trajectories from adulthood into old age

BACKGROUND: Frailty is a complex, dynamic geriatric condition, but limited evidence has shown how genes and environment may contribute to its longitudinal changes. We sought to investigate sources of individual differences in the longitudinal trajectories of frailty, considering potential selection bias when including a sample of oldest-old twins. METHODS: Data were from two Swedish twin cohort studies: a younger cohort comprising 1,842 adults aged 29-96 years followed up to 15 waves, and an older cohort comprising 654 adults aged ≥79 years followed up to five waves. Frailty was measured using the frailty index (FI). Age-based latent growth curve models were used to examine longitudinal trajectories, and extended to a biometric analysis to decompose variability into genetic and environmental etiologies. RESULTS: A bilinear model with an inflection point at age 75 best described the data, indicating a four- to five-fold faster FI increase after 75 years. Twins from the older cohort had significantly higher mean FI at baseline but slower rate of increase afterwards. FI level at age 75 was moderately heritable in both men (42%) and women (55%). Genetic influences were relatively stable across age for men and increasing for women, although the most salient amplification in FI variability after age 75 was due to individual-specific environmental influences for both men and women; conclusions were largely consistent when excluding the older cohort. CONCLUSION: Increased heterogeneity of frailty in late life is mainly attributable to environmental influences, highlighting the importance of targeting environmental risk factors to mitigate frailty in older adults.publishedVersionPeer reviewe