Medication reviews and deprescribing as a single intervention in falls prevention: a systematic review and meta-analysis

BACKGROUND: our aim was to assess the effectiveness of medication review and deprescribing interventions as a single intervention in falls prevention. METHODS:   DESIGN: systematic review and meta-analysis. DATA SOURCES: Medline, Embase, Cochrane CENTRAL, PsycINFO until 28 March 2022. ELIGIBILITY CRITERIA: randomised controlled trials of older participants comparing any medication review or deprescribing intervention with usual care and reporting falls as an outcome. STUDY RECORDS: title/abstract and full-text screening by two reviewers. RISK OF BIAS: Cochrane Collaboration revised tool. DATA SYNTHESIS: results reported separately for different settings and sufficiently comparable studies meta-analysed. RESULTS: forty-nine heterogeneous studies were included. COMMUNITY: meta-analyses of medication reviews resulted in a risk ratio (RR) of 1.05 (95% confidence interval, 0.85–1.29, I(2) = 0%, 3 studies(s)) for number of fallers, in an RR = 0.95 (0.70–1.27, I(2) = 37%, 3 s) for number of injurious fallers and in a rate ratio (RaR) of 0.89 (0.69–1.14, I(2) = 0%, 2 s) for injurious falls. HOSPITAL: meta-analyses assessing medication reviews resulted in an RR = 0.97 (0.74–1.28, I(2) = 15%, 2 s) and in an RR = 0.50 (0.07–3.50, I(2) = 72% %, 2 s) for number of fallers after and during admission, respectively. LONG-TERM CARE: meta-analyses investigating medication reviews or deprescribing plans resulted in an RR = 0.86 (0.72–1.02, I(2) = 0%, 5 s) for number of fallers and in an RaR = 0.93 (0.64–1.35, I(2) = 92%, 7 s) for number of falls. CONCLUSIONS: the heterogeneity of the interventions precluded us to estimate the exact effect of medication review and deprescribing as a single intervention. For future studies, more comparability is warranted. These interventions should not be implemented as a stand-alone strategy in falls prevention but included in multimodal strategies due to the multifactorial nature of falls. PROSPERO registration number: CRD4202021823

Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events

The Molecular Genetic Architecture of Self-Employment

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2= 25%, h2= 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10-5were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases

Genome-wide association studies of cerebral white matter lesion burden: The CHARGE consortium

White matter hyperintensities (WMH) detectable by magnetic resonance imaging (MRI)are part of the spectrum of vascular injury associated with aging of the brain and are thought to reflect ischemic damage to the small deep cerebral vessels. WMH are associated with an increased risk of cognitive and motor dysfunction, dementia, depression, and stroke. Despite a significant heritability, few genetic loci influencing WMH burden have been identified

Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.</p

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

Causal effect of plasminogen activator inhibitor type 1 on coronary heart disease

Background--Plasminogen activator inhibitor type 1 (PAI-1) plays an essential role in the fibrinolysis system and thrombosis. Population studies have reported that blood PAI-1 levels are associated with increased risk of coronary heart disease (CHD). However, it is unclear whether the association reflects a causal influence of PAI-1 on CHD risk. Methods and Results--To evaluate the association between PAI-1 and CHD, we applied a 3-step strategy. First, we investigated the observational association between PAI-1 and CHD incidence using a systematic review based on a literature search for PAI-1 and CHD studies. Second, we explored the causal association between PAI-1 and CHD using a Mendelian randomization approach using summary statistics from large genome-wide association studies. Finally, we explored the causal effect of PAI-1 on cardiovascular risk factors including metabolic and subclinical atherosclerosis measures. In the systematic meta-analysis, the highest quantile of blood PAI-1 level was associated with higher CHD risk comparing with the lowest quantile (odds ratio=2.17; 95% CI: 1.53, 3.07) in an age- and sex-adjusted model. The effect size was reduced in studies using a multivariable-adjusted model (odds ratio=1.46; 95% CI: 1.13, 1.88). The Mendelian randomization analyses suggested a causal effect of increased PAI-1 level on CHD risk (odds ratio=1.22 per unit increase of log-transformed PAI-1; 95% CI: 1.01, 1.47). In addition, we also detected a causal effect of PAI-1 on elevating blood glucose and high-density lipoprotein cholesterol. Conclusions--Our study indicates a causal effect of elevated PAI-1 level on CHD risk, which may be mediated by glucose dysfunction

The Molecular Genetic Architecture of Self-Employment

Peer reviewe

Author Correction:Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article

Genome-wide association study identifies 74 loci associated with educational attainment

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases