The aim of this study was to systematically collate and appraise the available evidence regarding the associations between small, dense low-density lipoprotein (sdLDL) and incident coronary heart ...disease (CHD), focusing on cholesterol concentration (sdLDL-C) and sdLDL particle characteristics (presence, density, and size).
Coronary heart disease (CHD) is the leading cause of death worldwide. Small, dense low-density lipoprotein (sdLDL) has been hypothesized to induce atherosclerosis and subsequent coronary heart disease (CHD). However, the etiological relevance of lipoprotein particle size (sdLDL) versus cholesterol content (sdLDL-C) remains unclear.
PubMed, MEDLINE, Web of Science, and EMBASE were systematically searched for studies published before February 2020. CHD associations were based on quartile comparisons in eight studies of sdLDL-C and were based on binary categorization in fourteen studies of sdLDL particle size. Reported hazards ratios (HR) and odds ratios (OR) with 95% confidence interval (CI) were standardized and pooled using a random-effects meta-analysis model.
Data were collated from 21 studies with a total of 30,628 subjects and 5,693 incident CHD events. The average age was 67 years, and 53% were men. Higher sdLDL and sdLDL-C levels were both significantly associated with higher risk of CHD. The pooled estimate for the high vs. low categorization of sdLDL was 1.36 (95% CI: 1.21, 1.52) and 1.07 (95% CI: 1.01, 1.12) for comparing the top quartiles versus the bottom of sdLDL-C. Several studies suggested a dose response relationship.
The findings show a positive association between sdLDL or sdLDL-C levels and CHD, which is supported by an increasing body of genetic evidence in favor of its causality as an etiological risk factor. Thus, the results support sdLDL and sdLDL-C as a risk marker, but further research is required to establish sdLDL or sdLDL-C as a potential therapeutic marker for incident CHD risk reduction.
AbstractObjectiveTo investigate the shape of the causal relation between body mass index (BMI) and mortality.DesignLinear and non-linear mendelian randomisation analyses.SettingNord-Trøndelag Health ...(HUNT) Study (Norway) and UK Biobank (United Kingdom).ParticipantsMiddle to early late aged participants of European descent: 56 150 from the HUNT Study and 366 385 from UK Biobank.Main outcome measuresAll cause and cause specific (cardiovascular, cancer, and non-cardiovascular non-cancer) mortality.Results12 015 and 10 344 participants died during a median of 18.5 and 7.0 years of follow-up in the HUNT Study and UK Biobank, respectively. Linear mendelian randomisation analyses indicated an overall positive association between genetically predicted BMI and the risk of all cause mortality. An increase of 1 unit in genetically predicted BMI led to a 5% (95% confidence interval 1% to 8%) higher risk of mortality in overweight participants (BMI 25.0-29.9) and a 9% (4% to 14%) higher risk of mortality in obese participants (BMI ≥30.0) but a 34% (16% to 48%) lower risk in underweight (BMI <18.5) and a 14% (−1% to 27%) lower risk in low normal weight participants (BMI 18.5-19.9). Non-linear mendelian randomisation indicated a J shaped relation between genetically predicted BMI and the risk of all cause mortality, with the lowest risk at a BMI of around 22-25 for the overall sample. Subgroup analyses by smoking status, however, suggested an always-increasing relation of BMI with mortality in never smokers and a J shaped relation in ever smokers.ConclusionsThe previously observed J shaped relation between BMI and risk of all cause mortality appears to have a causal basis, but subgroup analyses by smoking status revealed that the BMI-mortality relation is likely comprised of at least two distinct curves, rather than one J shaped relation. An increased risk of mortality for being underweight was only evident in ever smokers.
Americans have a shorter life expectancy compared with residents of almost all other high-income countries. We aim to estimate the impact of lifestyle factors on premature mortality and life ...expectancy in the US population.
Using data from the Nurses' Health Study (1980-2014; n=78 865) and the Health Professionals Follow-up Study (1986-2014, n=44 354), we defined 5 low-risk lifestyle factors as never smoking, body mass index of 18.5 to 24.9 kg/m
, ≥30 min/d of moderate to vigorous physical activity, moderate alcohol intake, and a high diet quality score (upper 40%), and estimated hazard ratios for the association of total lifestyle score (0-5 scale) with mortality. We used data from the NHANES (National Health and Nutrition Examination Surveys; 2013-2014) to estimate the distribution of the lifestyle score and the US Centers for Disease Control and Prevention WONDER database to derive the age-specific death rates of Americans. We applied the life table method to estimate life expectancy by levels of the lifestyle score.
During up to 34 years of follow-up, we documented 42 167 deaths. The multivariable-adjusted hazard ratios for mortality in adults with 5 compared with zero low-risk factors were 0.26 (95% confidence interval CI, 0.22-0.31) for all-cause mortality, 0.35 (95% CI, 0.27-0.45) for cancer mortality, and 0.18 (95% CI, 0.12-0.26) for cardiovascular disease mortality. The population-attributable risk of nonadherence to 5 low-risk factors was 60.7% (95% CI, 53.6-66.7) for all-cause mortality, 51.7% (95% CI, 37.1-62.9) for cancer mortality, and 71.7% (95% CI, 58.1-81.0) for cardiovascular disease mortality. We estimated that the life expectancy at age 50 years was 29.0 years (95% CI, 28.3-29.8) for women and 25.5 years (95% CI, 24.7-26.2) for men who adopted zero low-risk lifestyle factors. In contrast, for those who adopted all 5 low-risk factors, we projected a life expectancy at age 50 years of 43.1 years (95% CI, 41.3-44.9) for women and 37.6 years (95% CI, 35.8-39.4) for men. The projected life expectancy at age 50 years was on average 14.0 years (95% CI, 11.8-16.2) longer among female Americans with 5 low-risk factors compared with those with zero low-risk factors; for men, the difference was 12.2 years (95% CI, 10.1-14.2).
Adopting a healthy lifestyle could substantially reduce premature mortality and prolong life expectancy in US adults.
Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK ...Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.
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•Genome-wide association study interrogates 36 traits across the hematopoietic system•A total of 2,706 associated variants, including 130 rare and 230 low frequency•Describes allelic spectrum and heritability of coding and regulatory variants•Unravels causal contributions to cardiovascular, immune, and psychiatric disease
As part of the IHEC Consortium, this study probes the allelic architecture and regulatory landscape of cellular complex traits with power to identify causal pathways and links to diseases such as schizophrenia. Explore the Cell Press IHEC web portal at http://www.cell.com/consortium/IHEC.
Osteoporosis is a common aging-related disease diagnosed primarily using bone mineral density (BMD). We assessed genetic determinants of BMD as estimated by heel quantitative ultrasound in 426,824 ...individuals, identifying 518 genome-wide significant loci (301 novel), explaining 20% of its variance. We identified 13 bone fracture loci, all associated with estimated BMD (eBMD), in ~1.2 million individuals. We then identified target genes enriched for genes known to influence bone density and strength (maximum odds ratio (OR) = 58, P = 1 × 10
) from cell-specific features, including chromatin conformation and accessible chromatin sites. We next performed rapid-throughput skeletal phenotyping of 126 knockout mice with disruptions in predicted target genes and found an increased abnormal skeletal phenotype frequency compared to 526 unselected lines (P < 0.0001). In-depth analysis of one gene, DAAM2, showed a disproportionate decrease in bone strength relative to mineralization. This genetic atlas provides evidence linking associated SNPs to causal genes, offers new insight into osteoporosis pathophysiology, and highlights opportunities for drug development.
Summary Background Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of ...prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up. Methods Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4–14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5–<25·0 kg/m2. Findings All-cause mortality was minimal at 20·0–25·0 kg/m2 (HR 1·00, 95% CI 0·98–1·02 for BMI 20·0–<22·5 kg/m2 ; 1·00, 0·99–1·01 for BMI 22·5–<25·0 kg/m2 ), and increased significantly both just below this range (1·13, 1·09–1·17 for BMI 18·5–<20·0 kg/m2 ; 1·51, 1·43–1·59 for BMI 15·0–<18·5) and throughout the overweight range (1·07, 1·07–1·08 for BMI 25·0–<27·5 kg/m2 ; 1·20, 1·18–1·22 for BMI 27·5–<30·0 kg/m2 ). The HR for obesity grade 1 (BMI 30·0–<35·0 kg/m2 ) was 1·45, 95% CI 1·41–1·48; the HR for obesity grade 2 (35·0–<40·0 kg/m2 ) was 1·94, 1·87–2·01; and the HR for obesity grade 3 (40·0–<60·0 kg/m2 ) was 2·76, 2·60–2·92. For BMI over 25·0 kg/m2 , mortality increased approximately log-linearly with BMI; the HR per 5 kg/m2 units higher BMI was 1·39 (1·34–1·43) in Europe, 1·29 (1·26–1·32) in North America, 1·39 (1·34–1·44) in east Asia, and 1·31 (1·27–1·35) in Australia and New Zealand. This HR per 5 kg/m2 units higher BMI (for BMI over 25 kg/m2 ) was greater in younger than older people (1·52, 95% CI 1·47–1·56, for BMI measured at 35–49 years vs 1·21, 1·17–1·25, for BMI measured at 70–89 years; pheterogeneity <0·0001), greater in men than women (1·51, 1·46–1·56, vs 1·30, 1·26–1·33; pheterogeneity <0·0001), but similar in studies with self-reported and measured BMI. Interpretation The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations. Funding UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health.
By sustaining transmission or causing malaria outbreaks, imported malaria undermines malaria elimination efforts. Few studies have examined the impact of travel on malaria epidemiology. We conducted ...a literature review and meta-analysis of studies investigating travel as a risk factor for malaria infection in sub-Saharan Africa using PubMed. We identified 22 studies and calculated a random-effects meta-analysis pooled odds ratio (OR) of 3.77 (95% CI: 2.49-5.70), indicating that travel is a significant risk factor for malaria infection. Odds ratios were particularly high in urban locations when travel was to rural areas, to more endemic/high transmission areas, and in young children. Although there was substantial heterogeneity in the magnitude of association across the studies, the pooled estimate and directional consistency support travel as an important risk factor for malaria infection.
Abstract
Aims
The aim of this study was to derive and validate the SCORE2-Older Persons (SCORE2-OP) risk model to estimate 5- and 10-year risk of cardiovascular disease (CVD) in individuals aged ...over 70 years in four geographical risk regions.
Methods and results
Sex-specific competing risk-adjusted models for estimating CVD risk (CVD mortality, myocardial infarction, or stroke) were derived in individuals aged over 65 without pre-existing atherosclerotic CVD from the Cohort of Norway (28 503 individuals, 10 089 CVD events). Models included age, smoking status, diabetes, systolic blood pressure, and total- and high-density lipoprotein cholesterol. Four geographical risk regions were defined based on country-specific CVD mortality rates. Models were recalibrated to each region using region-specific estimated CVD incidence rates and risk factor distributions. For external validation, we analysed data from 6 additional study populations {338 615 individuals, 33 219 CVD validation cohorts, C-indices ranged between 0.63 95% confidence interval (CI) 0.61–0.65 and 0.67 (0.64–0.69)}. Regional calibration of expected-vs.-observed risks was satisfactory. For given risk factor profiles, there was substantial variation across the four risk regions in the estimated 10-year CVD event risk.
Conclusions
The competing risk-adjusted SCORE2-OP model was derived, recalibrated, and externally validated to estimate 5- and 10-year CVD risk in older adults (aged 70 years or older) in four geographical risk regions. These models can be used for communicating the risk of CVD and potential benefit from risk factor treatment and may facilitate shared decision-making between clinicians and patients in CVD risk management in older persons.
Graphical Abstract
Development process, risk regions and illustrative example for the SCORE2-OP algorithm.
It is uncertain whether depressive symptoms are independently associated with subsequent risk of cardiovascular diseases (CVDs).
To characterize the association between depressive symptoms and CVD ...incidence across the spectrum of lower mood.
A pooled analysis of individual-participant data from the Emerging Risk Factors Collaboration (ERFC; 162 036 participants; 21 cohorts; baseline surveys, 1960-2008; latest follow-up, March 2020) and the UK Biobank (401 219 participants; baseline surveys, 2006-2010; latest follow-up, March 2020). Eligible participants had information about self-reported depressive symptoms and no CVD history at baseline.
Depressive symptoms were recorded using validated instruments. ERFC scores were harmonized across studies to a scale representative of the Center for Epidemiological Studies Depression (CES-D) scale (range, 0-60; ≥16 indicates possible depressive disorder). The UK Biobank recorded the 2-item Patient Health Questionnaire 2 (PHQ-2; range, 0-6; ≥3 indicates possible depressive disorder).
Primary outcomes were incident fatal or nonfatal coronary heart disease (CHD), stroke, and CVD (composite of the 2). Hazard ratios (HRs) per 1-SD higher log CES-D or PHQ-2 adjusted for age, sex, smoking, and diabetes were reported.
Among 162 036 participants from the ERFC (73%, women; mean age at baseline, 63 years SD, 9 years), 5078 CHD and 3932 stroke events were recorded (median follow-up, 9.5 years). Associations with CHD, stroke, and CVD were log linear. The HR per 1-SD higher depression score for CHD was 1.07 (95% CI, 1.03-1.11); stroke, 1.05 (95% CI, 1.01-1.10); and CVD, 1.06 (95% CI, 1.04-1.08). The corresponding incidence rates per 10 000 person-years of follow-up in the highest vs the lowest quintile of CES-D score (geometric mean CES-D score, 19 vs 1) were 36.3 vs 29.0 for CHD events, 28.0 vs 24.7 for stroke events, and 62.8 vs 53.5 for CVD events. Among 401 219 participants from the UK Biobank (55% were women, mean age at baseline, 56 years SD, 8 years), 4607 CHD and 3253 stroke events were recorded (median follow-up, 8.1 years). The HR per 1-SD higher depression score for CHD was 1.11 (95% CI, 1.08-1.14); stroke, 1.10 (95% CI, 1.06-1.14); and CVD, 1.10 (95% CI, 1.08-1.13). The corresponding incidence rates per 10 000 person-years of follow-up among individuals with PHQ-2 scores of 4 or higher vs 0 were 20.9 vs 14.2 for CHD events, 15.3 vs 10.2 for stroke events, and 36.2 vs 24.5 for CVD events. The magnitude and statistical significance of the HRs were not materially changed after adjustment for additional risk factors.
In a pooled analysis of 563 255 participants in 22 cohorts, baseline depressive symptoms were associated with CVD incidence, including at symptom levels lower than the threshold indicative of a depressive disorder. However, the magnitude of associations was modest.
Although previous studies have shown that frequent ventricular premature complexes (VPCs) in patients with established heart disease are associated with increased risk of cardiac mortality, the ...significance of VPCs in general populations is unclear. The aim of this study was to assess the association between VPCs and risk of sudden cardiac death or total cardiac death in general populations by conducting a meta-analysis of published research. The electronic databases MEDLINE and Embase were searched for relevant studies. Data were abstracted using standardized forms. Study-specific relative risk estimates were pooled using a random-effects meta-analysis model. Eleven studies comprising a total of 106,195 participants sampled from general populations were included. Studies generally defined frequent VPCs as occurring ≥1 time during a standard electrocardiographic recording or ≥30 times over a 1-hour recording. The prevalence of frequent VPCs in the studies ranged from 1.2% to 10.7%. The overall adjusted relative risk for sudden cardiac death comparing participants with frequent VPCs versus those without frequent VPCs was 2.64 (95% confidence interval 1.93 to 3.63). The corresponding value for total cardiac death was 2.07 (95% confidence interval 1.71 to 2.50). Although most studies made attempts to exclude high-risk subjects, such as those with histories of cardiovascular disease, they did not test participants for underlying structural heart disease. In conclusion, findings from observational studies in general populations indicate that frequent VPCs are associated with a substantial increase in the risk for sudden cardiac death and total cardiac death. Further study is needed to determine the role of confounding and underlying structural heart disease in the observed association and its utility in cardiovascular risk prediction.
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