Comment on "A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk"

A 27-protein signature has been proposed to predict cardiovascular disease, but its applicability in clinical decision-making remains unclear

Immune system-wide Mendelian randomization and triangulation analyses support autoimmunity as a modifiable component in dementia-causing diseases

Publisher Copyright: © 2022, The Author(s).Immune system and blood–brain barrier dysfunction are implicated in the development of Alzheimer’s and other dementia-causing diseases, but their causal role remains unknown. We performed Mendelian randomization for 1,827 immune system- and blood–brain barrier-related biomarkers and identified 127 potential causal risk factors for dementia-causing diseases. Pathway analyses linked these biomarkers to amyloid-β, tau and α-synuclein pathways and to autoimmunity-related processes. A phenome-wide analysis using Mendelian randomization-based polygenic risk score in the FinnGen study (n = 339,233) for the biomarkers indicated shared genetic background for dementias and autoimmune diseases. This association was further supported by human leukocyte antigen analyses. In inverse-probability-weighted analyses that simulate randomized controlled drug trials in observational data, anti-inflammatory methotrexate treatment reduced the incidence of Alzheimer’s disease in high-risk individuals (hazard ratio compared with no treatment, 0.64, 95% confidence interval 0.49–0.88, P = 0.005). These converging results from different lines of human research suggest that autoimmunity is a modifiable component in dementia-causing diseases.Peer reviewe

Systematic comparison of family history and polygenic risk across 24 common diseases

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Physical activity associates with subarachnoid hemorrhage risk– a population-based long-term cohort study

Benefit of physical activity in prevention of aneurysmal subarachnoid hemorrhage (SAH) is unclear. We aimed to clarify this by studying how different types of physical activity associate with SAH risk. By following 65 521 population-based FINRISK participants prospectively from medical and autopsy registries since 1972 until 2014, we detected 543 incident SAHs. At baseline, we measured leisure-time physical activity (LTPA), occupational physical activity (OPA), and commuting physical activity (CPA) levels. The Cox model adjusted for all well-known SAH risk factors and for socioeconomic status, provided hazard ratios (HRs) for physical activity variables. Every 30-minute increase in weekly LTPA decreased SAH risk linearly in men and women HR = 0.95 (95% CI = 0.90–1.00). CPA reduced SAH risk as well, but the association diminished as participants retired. In contrast, individuals with moderate (1.41, 1.04–1.92) and high OPA (1.34, 0.99–1.81) had elevated SAH risk. Protective association of LTPA persisted in all age and hypertension groups, and was even greater in current smokers 0.88 (0.81–0.96) than non-smokers (p = 0.04 for difference). Commuting and leisure time physical activity seem to reduce SAH risk in men and women and is most beneficial for smokers. Future intervention studies should investigate whether physical activity can reduce the rupture risk of intracranial aneurysms.Peer reviewe

Risk of Macrovascular and Microvascular Disease in Diabetes Diagnosed Using Oral Glucose Tolerance Test With and Without Confirmation by Hemoglobin A1c : The Whitehall II Cohort Study

Background: It is unclear whether replacing oral glucose tolerance test (OGTT) with hemoglobin A1c (HbA1c) measurement for diagnosing diabetes is justified. We aimed to assess the proportion of OGTT-diagnosed diabetes cases that can be confirmed by HbA1c and to examine whether individuals with OGTT diagnosis but nondiagnostic HbA1c are at higher risk of macrovascular and microvascular disease. Methods: Participants were 5773 men and women from the population-based Whitehall II prospective cohort study in the United Kingdom. New OGTT diabetes cases diagnosed in clinical examinations in 2002 to 2004 and 2007 to 2009 were assessed for HbA1c confirmation (>= 6.5%) in these and subsequent clinical examinations in 2012 to 2013 and 2015 to 2016. All participants were followed up for major cardiovascular events through linkage to electronic health records until 2017 and for incident chronic kidney disease (estimated glomerular filtration ratePeer reviewe

Obesity and risk of diseases associated with hallmarks of cellular ageing: a multicohort study

BACKGROUND: Ageing hallmarks, characterising features of cellular ageing, have a role in the pathophysiology of many age-related diseases. We examined whether obesity is associated with an increased risk of developing such hallmark-related diseases. METHODS: In this multicohort study, we included people aged 38-72 years with data on weight, height, and waist circumference measured during a clinical examination at baseline between March 13, 2006, and Oct 1, 2010, from the UK Biobank with follow-up until Nov 12, 2021. To test reproducibility of the findings (replication analysis), we used data from people aged 40 years or older included in the Finnish Public Sector study and the Finnish Health and Social Support study who responded to the study surveys, had data on BMI, and were successfully linked to electronic health records from national registers up to Dec 31, 2016. Obesity and clinical characteristics were assessed at baseline. Via linkage to national health records, participants were followed up for 83 diseases related to nine ageing hallmarks (genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication). Outcomes were the first instance of hallmark-related disease, in addition to co-occurrence of three or more hallmark-related diseases and mortality. FINDINGS: 496 530 adults (mean age 57·0 years [SD 8·1]) from the UK Biobank were included in the primary analysis, and 83 249 (mean age 48·2 years [6·4]) adults from the Finnish cohorts were included in the replication analysis. Median follow-up was 12·7 years (IQR 12·0-13·4) in the UK Biobank and 14·0 years (8·0-15·0) in the Finnish cohorts. After adjusting for demographic characteristics, lifestyle factors, and depression, UK Biobank participants with obesity (BMI ≥30·0 kg/m2) had a 1·40 (95% CI 1·38-1·41) times higher hazard ratio for the first hallmark-related disease than those with a healthy weight (BMI 18·5-24·9 kg/m2). The corresponding hazard ratios for three co-occurring diseases were 2·92 (95% CI 2·64-3·22) for deregulated nutrient sensing, 2·73 (2·46-3·02) for telomere attrition, 2·33 (2·10-2·60) for epigenetic alterations, 2·30 (2·14-2·48) for mitochondrial dysfunction, 2·23 (2·04-2·45) for stem cell exhaustion, 2·02 (1·89-2·16) for altered intercellular communication, 2·01 (1·89-2·15) for cellular senescence, 1·83 (1·67-2·00) for loss of proteostasis, and 1·39 (1·27-1·52) for genomic instability. These findings were replicated in the Finnish cohorts. In both studies, the associations between other risk factors (low education, unhealthy dietary factors [available only in the UK Biobank], smoking, high alcohol consumption, physical inactivity, and depression) and hallmark-related diseases were weaker than those with obesity. 45-60% of the excess mortality in people with obesity was attributable to hallmark-related diseases. INTERPRETATION: Obesity might have an important role in the development of diseases associated with cellular ageing. Tackling ageing mechanisms could potentially help to reduce the disease and mortality burden resulting from the obesity epidemic. FUNDING: Wellcome Trust, UK Medical Research Council, US National Institute on Aging, Academy of Finland, and Finnish Foundation for Cardiovascular Research. TRANSLATIONS: For the German and Finnish translations of the abstract see Supplementary Materials section

Long‐term risk of dementia following hospitalization due to physical diseases: A multicohort study

Introduction Conventional risk factors targeted by prevention (e.g., low education, smoking, and obesity) are associated with a 1.2‐ to 2‐fold increased risk of dementia. It is unclear whether having a physical disease is an equally important risk factor for dementia. Methods In this exploratory multicohort study of 283,414 community‐dwelling participants, we examined 22 common hospital‐treated physical diseases as risk factors for dementia. Results During a median follow‐up of 19 years, a total of 3416 participants developed dementia. Those who had erysipelas (hazard ratio = 1.82; 95% confidence interval = 1.53 to 2.17), hypothyroidism (1.94; 1.59 to 2.38), myocardial infarction (1.41; 1.20 to 1.64), ischemic heart disease (1.32; 1.18 to 1.49), cerebral infarction (2.44; 2.14 to 2.77), duodenal ulcers (1.88; 1.42 to 2.49), gastritis and duodenitis (1.82; 1.46 to 2.27), or osteoporosis (2.38; 1.75 to 3.23) were at a significantly increased risk of dementia. These associations were not explained by conventional risk factors or reverse causation. Discussion In addition to conventional risk factors, several physical diseases may increase the long‐term risk of dementia.Peer reviewe

Aortic Pulse Wave Velocity as Adjunct Risk Marker for Assessing Cardiovascular Disease Risk : Prospective Study

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Estimating Dementia Risk Using Multifactorial Prediction Models

IMPORTANCE: The clinical value of current multifactorial algorithms for individualized assessment of dementia risk remains unclear. OBJECTIVE: To evaluate the clinical value associated with 4 widely used dementia risk scores in estimating 10-year dementia risk. DESIGN, SETTING, AND PARTICIPANTS: This prospective population-based UK Biobank cohort study assessed 4 dementia risk scores at baseline (2006-2010) and ascertained incident dementia during the following 10 years. Replication with a 20-year follow-up was based on the British Whitehall II study. For both analyses, participants who had no dementia at baseline, had complete data on at least 1 dementia risk score, and were linked to electronic health records from hospitalizations or mortality were included. Data analysis was conducted from July 5, 2022, to April 20, 2023. EXPOSURES: Four existing dementia risk scores: the Cardiovascular Risk Factors, Aging and Dementia (CAIDE)-Clinical score, the CAIDE-APOE-supplemented score, the Brief Dementia Screening Indicator (BDSI), and the Australian National University Alzheimer Disease Risk Index (ANU-ADRI). MAIN OUTCOMES AND MEASURES: Dementia was ascertained from linked electronic health records. To evaluate how well each score predicted the 10-year risk of dementia, concordance (C) statistics, detection rate, false-positive rate, and the ratio of true to false positives were calculated for each risk score and for a model including age alone. RESULTS: Of 465 929 UK Biobank participants without dementia at baseline (mean [SD] age, 56.5 [8.1] years; range, 38-73 years; 252 778 [54.3%] female participants), 3421 were diagnosed with dementia at follow-up (7.5 per 10 000 person-years). If the threshold for a positive test result was calibrated to achieve a 5% false-positive rate, all 4 risk scores detected 9% to 16% of incident dementia and therefore missed 84% to 91% (failure rate). The corresponding failure rate was 84% for a model that included age only. For a positive test result calibrated to detect at least half of future incident dementia, the ratio of true to false positives ranged between 1 to 66 (for CAIDE-APOE-supplemented) and 1 to 116 (for ANU-ADRI). For age alone, the ratio was 1 to 43. The C statistic was 0.66 (95% CI, 0.65-0.67) for the CAIDE clinical version, 0.73 (95% CI, 0.72-0.73) for the CAIDE-APOE-supplemented, 0.68 (95% CI, 0.67-0.69) for BDSI, 0.59 (95% CI, 0.58-0.60) for ANU-ADRI, and 0.79 (95% CI, 0.79-0.80) for age alone. Similar C statistics were seen for 20-year dementia risk in the Whitehall II study cohort, which included 4865 participants (mean [SD] age, 54.9 [5.9] years; 1342 [27.6%] female participants). In a subgroup analysis of same-aged participants aged 65 (±1) years, discriminatory capacity of risk scores was low (C statistics between 0.52 and 0.60). CONCLUSIONS AND RELEVANCE: In these cohort studies, individualized assessments of dementia risk using existing risk prediction scores had high error rates. These findings suggest that the scores were of limited value in targeting people for dementia prevention. Further research is needed to develop more accurate algorithms for estimation of dementia risk

Body-mass index and risk of obesity-related complex multimorbidity: an observational multicohort study

BACKGROUND: The accumulation of disparate diseases in complex multimorbidity makes prevention difficult if each disease is targeted separately. We aimed to examine obesity as a shared risk factor for common diseases, determine associations between obesity-related diseases, and examine the role of obesity in the development of complex multimorbidity (four or more comorbid diseases). METHODS: We did an observational study and used pooled prospective data from two Finnish cohort studies (the Health and Social Support Study and the Finnish Public Sector Study) comprising 114 657 adults aged 16-78 years at study entry (1998-2013). A cohort of 499 357 adults (aged 38-73 years at study entry; 2006-10) from the UK Biobank provided replication in an independent population. BMI and clinical characteristics were assessed at baseline. BMIs were categorised as obesity (≥30·0 kg/m2), overweight (25·0-29·9 kg/m2), healthy weight (18·5-24·9 kg/m2), and underweight (<18·5 kg/m2). Via linkage to national health records, participants were followed-up for death and diseases diagnosed according to the International Classification of Diseases 10th Revision (ICD-10). Hazard ratios (HRs) with 95% CIs and population attributable fractions (PAFs) for associations between BMI and multimorbidity were calculated. FINDINGS: Mean follow-up duration was 12·1 years (SD 3·8) in the Finnish cohorts and 11·8 years (1·7) in the UK Biobank cohort. Obesity was associated with 21 non-overlapping cardiometabolic, digestive, respiratory, neurological, musculoskeletal, and infectious diseases after Bonferroni multiple testing adjustment and ignoring HRs of less than 1·50. Compared with healthy weight, the confounder-adjusted HR for obesity was 2·83 (95% CI 2·74-2·93; PAF 19·9% [95% CI 19·3-20·5]) for developing at least one obesity-related disease, 5·17 (4·84-5·53; 34·4% [33·2-35·5]) for two diseases, and 12·39 (9·26-16·58; 55·2% [50·9-57·5]) for complex multimorbidity. The proportion of participants of healthy weight with complex multimorbidity by age 75 years was observed by age 55 years in participants with obesity, and degree of obesity was associated with complex multimorbidity in a dose-response relationship. Compared with obesity, the association between overweight and complex multimorbidity was more modest (HR 2·67, 95% CI 1·94-3·68; PAF 13·3% [95% CI 9·6-16·3]). The same pattern of results was observed in the UK Biobank cohort. INTERPRETATION: Obesity is associated with diverse, increasing disease burdens, and might represent an important target for multimorbidity prevention that avoids the complexities of multitarget preventive regimens. FUNDING: Wellcome Trust, Medical Research Council, National Institute on Aging