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ObjectiveMinimum joint space width (mJSW) from 2-dimensional images provides a proxy for cartilage thickness. This study aimed to conduct a genome-wide association study (GWAS) of mJSW to (i) identify new genetic determinants of mJSW and use them to (ii) examine causal effects of mJSW on hip osteoarthritis (HOA) risk.MethodsGWAS meta-analysis of hip mJSW derived from plain X-rays (four cohorts) or DXA (one cohort) was performed, stratified by sex and adjusted for age and ancestry principal components. Mendelian randomisation (MR) and cluster analyses were used to examine causal effect of mJSW on HOA.Results50,745 individuals were included in the meta-analysis. 42 SNPs, which mapped to 39 loci (35 novel), were identified. Mendelian randomisation (MR) revealed little evidence of a causal effect of mJSW on HOA (βIVW-0.01 [95% CI -0.19, 0.17]). However, MR-Clust analysis suggested the null MR estimates reflected the net effect of two distinct causal mechanisms cancelling each other out, one of which was protective, whereas the other increased HOA susceptibility. For the latter mechanism, all loci were positively associated with height, suggesting mechanisms leading to greater height and mJSW increase the risk of HOA in later life.ConclusionsGWAS and MR analyses suggested one group of mJSW loci reduces HOA risk via increased mJSW, suggesting possible utility as targets for chondroprotective therapies. The second group of mJSW loci increased HOA risk, despite increasing mJSW, but were also positively related to height, suggesting they contribute to mJSW and HOA risk via a growth-related mechanism.

STUDY OBJECTIVES: Subjective insomnia complaints and objective sleep changes are mostly studied outside of clinical trial studies. In this study, we tested whether 240 genetic variants associated with subjectively reported insomnia were also associated with objective insomnia parameters extracted from polysomnographic recordings in three studies. METHODS: The study sample (total n = 2,770) was composed of the Wisconsin Sleep Cohort (n = 1,091) and the Osteoporotic Fractures in Men (n = 1,026) study, two population-based studies, and the Stanford Sleep Cohort, a sleep center patient-based sample (n = 653). Seven objective polysomnographic features related to insomnia defined outcome variables, with each variant allele serving as predictor. Meta-regression was performed, accounting for common confounders as well as variance differences between studies. Additionally, a normalized genetic risk score was generated for each subject to serve as a predictor variable in separate linear mixed models assessing objective insomnia features. RESULTS: After correction for multiple testing, single-nucleotide polymorphisms associated with subjective insomnia were not significantly associated with 6 of 7 objective sleep measures. Only periodic limb movement index was significantly associated with rs113851554 (MEIS1), as found in previous studies. The normalized genetic risk score was only weakly associated with arousal index and duration of wake after sleep onset. CONCLUSIONS: Our findings suggest that subjective insomnia does not have a strong genetic signature mapping onto objective (polysomnographic) sleep variables. CITATION: Foldager J, Peppard PE, Hagen EW, et al. Genetic risk for subjective reports of insomnia associates only weakly with polygraphic measures of insomnia in 2,770 adults. J Clin Sleep Med. 2022;18(1):21-29.

Making drug development more efficient by identifying promising drug targets can contribute to resource savings. Identifying promising drug targets using human genetic approaches can remove barriers related to translation. In addition, genetic information can be used to identify potentially causal relationships between a drug target and disease. Mendelian randomization (MR) is a class of approaches used to identify causal associations between pairs of genetically predicted traits using data from human genetic studies. MR can be used to prioritize candidate drug targets by predicting disease outcomes and adverse events that could result from the manipulation of a drug target. The theory behind MR is reviewed, including a discussion of MR assumptions, different MR analytical methods, tests for violations of assumptions, and MR methods that can be robust to some violations of MR assumptions. A protocol to perform two-sample MR (2SMR) with summary genome-wide association study (GWAS) results is described. An example of 2SMR examining the causal relationship between low-density lipoprotein (LDL) and coronary artery disease (CAD) is provided as an illustration of the protocol.

Background Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing. Methods The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation Results We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10−8) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways. Conclusions We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

Study Objectives Periodic limb movement in sleep is a common sleep phenotype characterized by repetitive leg movements that occur during or before sleep. We conducted a genome-wide association study (GWAS) of periodic limb movements in sleep (PLMS) using a joint analysis (i.e., discovery, replication, and joint meta-analysis) of four cohorts (MrOS, the Wisconsin Sleep Cohort Study, HypnoLaus, and MESA), comprised of 6843 total subjects. Methods The MrOS study and Wisconsin Sleep Cohort Study (N = 1745 cases) were used for discovery. Replication in the HypnoLaus and MESA cohorts (1002 cases) preceded joint meta-analysis. We also performed LD score regression, estimated heritability, and computed genetic correlations between potentially associated traits such as restless leg syndrome (RLS) and insomnia. The causality and direction of the relationships between PLMS and RLS was evaluated using Mendelian randomization. Results We found 2 independent loci were significantly associated with PLMS: rs113851554 (p = 3.51 × 10−12, β = 0.486), an SNP located in a putative regulatory element of intron eight of MEIS1 (2p14); and rs9369062 (p = 3.06 × 10−22, β = 0.2093), a SNP located in the intron region of BTBD9 (6p12); both of which were also lead signals in RLS GWAS. PLMS is genetically correlated with insomnia, risk of stroke, and RLS, but not with iron deficiency. Pleiotropy adjusted Mendelian randomization analysis identified a causal effect of RLS on PLMS. Conclusions Because PLMS is more common than RLS, PLMS may have multiple causes and additional studies are needed to further validate these findings.

OBJECTIVE Disruption of rest-activity rhythms is cross-sectionally associated with metabolic disorders, including type 2 diabetes, yet it remains unclear whether it predicts impaired glucose metabolism and homeostasis. The aim of this study is to examine the cross-sectional and prospective associations between rest-activity rhythm characteristics and glycemic measures in a cohort of older men. RESEARCH DESIGN AND METHODS Baseline rest-activity rhythms were derived from actigraphy with use of extended cosine model analysis. With subjects fasting, glucose, insulin, and HOMA of insulin resistance (HOMA-IR) were measured from blood at baseline and after ∼3.5 years. Type 2 diabetes was defined based on self-report, medication use, and fasting glucose. RESULTS In the cross-sectional analysis (n = 2,450), lower 24-h amplitude-to-mesor ratio (i.e., mean activity-adjusted rhythm amplitude) and reduced overall rhythmicity were associated with higher fasting insulin and HOMA-IR (all Ptrend < 0.0001), indicating increased insulin resistance. The odds of baseline type 2 diabetes were significantly higher among those in the lowest quartile of amplitude (Q1) (odds ratio [OR]Q1 vs. Q4 1.63 [95% CI 1.14, 2.30]) and late acrophase group (ORlate vs. normal 1.46 [95% CI 1.04, 2.04]). In the prospective analysis (n = 861), multiple rest-activity characteristics predicted a two- to threefold increase in type 2 diabetes risk, including a lower amplitude (ORQ1 vs. Q4 3.81 [95% CI 1.45, 10.00]) and amplitude-to-mesor ratio (OR 2.79 [95% CI 1.10, 7.07]), reduced overall rhythmicity (OR 3.49 [95% CI 1.34, 9.10]), and a late acrophase (OR 2.44 [1.09, 5.47]). CONCLUSIONS Rest-activity rhythm characteristics are associated with impaired glycemic metabolism and homeostasis and higher risk of incident type 2 diabetes.

Identifying new genetic determinants of bone mineral density (BMD) and fracture promises to yield improved diagnostics and therapies for bone fragility. However, prioritizing candidate genes from genome-wide screens can be challenging. To overcome this challenge, we prioritized mouse genes that are differentially expressed in aging mouse bone based on whether their human homolog is associated with human BMD and/or fracture. Unbiased RNA-seq analysis of young and old male C57BL/6 mouse cortical bone identified 1499, 1685, and 5525 differentially expressed genes (DEGs) in 1, 2, and 2.5-year-old bone, relative to 2-month-old bone, respectively. Gene-based scores for heel ultrasound bone mineral density (eBMD) and fracture were estimated using published genome-wide association studies (GWAS) results of these traits in the UK Biobank. Enrichment analysis showed that mouse bone DEG sets for all three age groups, relative to young bone, are significantly enriched for eBMD, but only the oldest two DEG sets are enriched for fracture. Using gene-based scores, this approach prioritizes among thousands of DEGs by a factor of 5- to 100-fold, yielding 10 and 21 genes significantly associated with fracture in the two oldest groups of mouse DEGs. Though these genes were not the most differentially expressed, they included Sost, Lrp5, and others with well-established functions in bone. Several others have, as yet, unknown roles in the skeleton. Therefore, this study accelerates identification of new genetic determinants of bone fragility by prioritizing a clinically relevant and experimentally tractable number of candidate genes for functional analysis. Finally, we provide a website (www.mouse2human.org) to enable other researchers to easily apply our strategy. © 2022 American Society for Bone and Mineral Research (ASBMR).

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.

Background We developed a simple tool to estimate the probability of dying from acute COVID-19 illness only with readily available assessments at initial admission. Methods This retrospective study included 13,190 racially and ethnically diverse adults admitted to one of the New York City Health + Hospitals (NYC H+H) system for COVID-19 illness between March 1 and June 30, 2020. Demographic characteristics, simple vital signs and routine clinical laboratory tests were collected from the electronic medical records. A clinical prediction model to estimate the risk of dying during the hospitalization were developed. Results Mean age (interquartile range) was 58 (45–72) years; 5421 (41%) were women, 5258 were Latinx (40%), 3805 Black (29%), 1168 White (9%), and 2959 Other (22%). During hospitalization, 2,875 were (22%) died. Using separate test and validation samples, machine learning (Gradient Boosted Decision Trees) identified eight variables—oxygen saturation, respiratory rate, systolic and diastolic blood pressures, pulse rate, blood urea nitrogen level, age and creatinine—that predicted mortality, with an area under the ROC curve (AUC) of 94%. A score based on these variables classified 5,677 (46%) as low risk (a score of 0) who had 0.8% (95% confidence interval, 0.5–1.0%) risk of dying, and 674 (5.4%) as high-risk (score ≥ 12 points) who had a 97.6% (96.5–98.8%) risk of dying; the remainder had intermediate risks. A risk calculator is available online at https://danielevanslab.shinyapps.io/Covid_mortality/. Conclusions In a diverse population of hospitalized patients with COVID-19 illness, a clinical prediction model using a few readily available vital signs reflecting the severity of disease may precisely predict in-hospital mortality in diverse populations and can rapidly assist decisions to prioritize admissions and intensive care.

The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization (QRS duration) and repolarization (JT interval). Abnormalities of the QT interval are associated with potentially fatal ventricular arrhythmia. We conducted genome-wide multi-ancestry analyses in >250,000 individuals and identified 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identified associations with Mendelian disease genes. Enrichments were observed in established pathways for QT and JT, with new genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast, connective tissue components and processes for cell growth and extracellular matrix interactions were significantly enriched for QRS. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlighted potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization.

Skull bone mineral density (SK-BMD) provides a suitable trait for the discovery of genes important to bone biology in general, and particularly for identifying components unique to intramembranous ossification, which cannot be captured at other skeletal sites. We assessed genetic determinants of SK-BMD in 43,800 individuals, identifying 59 genome-wide significant loci (4 novel), explaining 12.5% of its variance. Pathway and enrichment analyses of the association signals resulted in clustering within gene-sets involved in regulating the development of the skeleton; overexpressed in the musculoskeletal system; and enriched in enhancer and transcribed regions in osteoblasts. From the four novel loci (mapping to ZIC1, PRKAR1A, ATP6V1C1, GLRX3), two (ZIC1 and PRKAR1A) have previously been related to craniofacial developmental defects. Functional validation of skull development in zebrafish revealed abnormal cranial bone initiation that culminated in ectopic sutures and reduced BMD in mutated zic1 and atp6v1c1 fish and asymmetric bone growth and elevated BMD in mutated prkar1a fish. We confirmed a role of ZIC1 loss-of-function in suture patterning and discovered ATP6V1C1 gene associated with suture development. In light of the evidence presented suggesting that SK-BMD is genetically related to craniofacial abnormalities, our study opens new avenues to the understanding of the pathophysiology of craniofacial defects and towards the effective pharmacological treatment of bone diseases.

Average arterial oxyhemoglobin saturation during sleep (AvSpO(2)S) is a clinically relevant measure of physiological stress associated with sleep-disordered breathing, and this measure predicts incident cardiovascular disease and mortality. Using high-depth whole-genome sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) project and focusing on genes with linkage evidence on chromosome 8p23,1, 2 we observed that six coding and 51 noncoding variants in a gene that encodes the GTPase-activating protein (DLC1) are significantly associated with AvSpO(2)S and replicated in independent subjects. The combined DLC1 association evidence of discovery and replication cohorts reaches genome-wide significance in European Americans (p = 7.9 × 10(−7)). A risk score for these variants, built on an independent dataset, explains 0.97% of the AvSpO(2)S variation and contributes to the linkage evidence. The 51 noncoding variants are enriched in regulatory features in a human lung fibroblast cell line and contribute to DLC1 expression variation. Mendelian randomization analysis using these variants indicates a significant causal effect of DLC1 expression in fibroblasts on AvSpO(2)S. Multiple sources of information, including genetic variants, gene expression, and methylation, consistently suggest that DLC1 is a gene associated with AvSpO(2)S.

Previous research has shown that genes play a substantial role in determining a person’s susceptibility to age-related hearing impairment. The existing studies on this subject have different results, which may be caused by difficulties in determining the phenotype or the limited number of participants involved. Here, we have gathered the largest sample to date (discovery n = 9,675; replication n = 10,963; validation n = 356,141), and examined phenotypes that represented low/mid and high frequency hearing loss on the pure tone audiogram. We identified 7 loci that were either replicated and/or validated, of which 5 loci are novel in hearing. Especially the ILDR1 gene is a high profile candidate, as it contains our top SNP, is a known hearing loss gene, has been linked to age-related hearing impairment before, and in addition is preferentially expressed within hair cells of the inner ear. By verifying all previously published SNPs, we can present a paper that combines all new and existing findings to date, giving a complete overview of the genetic architecture of age-related hearing impairment. This is of importance as age-related hearing impairment is highly prevalent in our ageing society and represents a large socio-economic burden.

Hip geometry (HG) is an important predictor of fracture. We performed a meta-analysis of GWAS studies in adults to identify genetic variants that are associated with proximal femur geometry phenotypes. We analyzed four phenotypes: 1) Femoral neck length; 2) Neck-shaft angle; 3) Femoral neck width, and 4) Femoral neck section modulus, estimated from DXA scans using algorithms of hip structure analysis. In the Discovery stage, 10 cohort studies were included in the fixed-effect meta-analysis, with up to 18,719 men and women ages 16-93 years. Association analyses were performed with ~ 2.5 million polymorphismsunder an additive model adjusted for age and body mass index; an additional analysis also adjusted for height. Replication analyses of meta-GWAS significant loci (at genome-wide significance, GWS, threshold p≤5x10-8) were performed in 7 additional cohorts in-silico. In meta-analysis not adjusting for height (combined Discovery and Replication stages), GWS associations were found on chr. 4 (in HHIP), chr. 8 (C8orf34), chr. 13 (FAM10A4 and DLEU2), and chr. 20 (inDDX27). The height-adjusted meta-analysis showed significant associations at 5p15 (IRX1 and ADAMTS16); 5q35 near FGFR4; at 12p11 (in CCDC91); 11q13 (near LRP5 and PPP6R3 (rs7102273)). Several HG signals overlapped with bone mineral density (BMD), including JAG1 on chr. 20, near TNFRSF11B (chr. 8), SOX6 and LRP5 (chr. 11). Chr. 11 SNP rs7102273 was associated with any-type fracture (p = 7.5 x 10-5). We used bone transcriptome data and discovered several significant eQTLs, including rs7102273 and PPP6R3 expression (p=0.0007), and rs6556301 (intergenic, chr.5) and PDLIM7 expression(p=0.005). In conclusion, we found associations between HG measures and several genes being part of biological pathways relevant to BMD and fractures. The results provide a defined set of genes facilitating further experimental exploration and validation to understand biological mechanisms underlying human bone geometry and etiology of bone fragility.

Background: Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass.Objectives: To determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci.Methods: We performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms).Results: Seven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as "sumo wrestler" loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed "body builder" loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in "body builder" loci were associated with metabolic protection.Conclusions: In conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass.

Chronic increases in pro-inflammatory cytokines in older adults, known as inflammaging, are an important risk factor for morbidity and mortality in the aging population. It has been suggested that circadian disruption may play a role in chronic inflammation, but there has been limited study that investigated the overall profile of 24-hour rest–activity rhythms in relation to inflammation using longitudinal data. In the Outcomes of Sleep Disorders in Older Men Study, we applied the extended cosine model to derive multiple rest–activity rhythm characteristics using multiday actigraphy, and examined their associations with 6 inflammatory markers (ie, C-reactive protein [CRP], interleukin 6 [IL-6], tumor necrosis factor alpha [TNF-α], tumor necrosis factor alpha soluble receptor II [TNF-α-sRII], interleukin-1β [IL-1β], interferon gamma [IFN-γ]) measured from fasting blood. We assessed both the cross-sectional association between rest–activity rhythms and inflammatory markers measured at baseline, and the prospective association between baseline rest–activity rhythms and changes in inflammatory markers over 3.5 years of follow-up. We found that multiple rest–activity characteristics, including lower amplitude and relative amplitude, and decreased overall rhythmicity, were associated with higher levels of CRP, IL-6, TNF-α, and TNF-α-sRII, but not IL-1β and IFN-γ at baseline. Moreover, the lowest quartile of these 3 rest–activity characteristics was associated with an approximately 2-fold increase in the odds of having elevated inflammation (ie, having 3 or more markers in the highest quartile) at baseline. However, we found little evidence supporting a relationship between rest–activity rhythm characteristics and changes in inflammatory markers. Future studies should clarify the dynamic relationship between rest–activity rhythms and inflammation in different populations, and evaluate the effects of improving rest–activity profiles on inflammation and related disease outcomes.

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

Prediction of mortality from COVID-19 infection might help triage patients to hospitalization and intensive care. To estimate the risk of inpatient mortality, we analyzed the data of 13,190 adult patients in the New York City Health + Hospitals system admitted for COVID-19 infection from March 1 to June 30, 2020. They had a mean age 58 years, 40% were Latinx, 29% Black, 9% White and 22% of other races/ethnicities and 2,875 died. We used Machine learning (Gradient Boosted Decision Trees; XGBoost) to select predictors of inpatient mortality from demographics, vital signs and lab tests results from initial encounters. XGBoost identified O2 saturation, systolic and diastolic blood pressure, pulse rate, respiratory rate, age, and BUN with an Area Under the Receiver Operating Characteristics Curve = 94%. We applied CART to find cut-points in these variables, logistic regression to calculate odds-ratios for those categories, and assigned points to the categories to develop a score. A score = 0 indicates a 0.8% (95% confidence interval, 0.5 – 1.0%) risk of dying and ≥ 12 points indicates a 98% (97-99%) risk, and other scores have intermediate risks. We translated the models into an online calculator for the probability of mortality with 95% confidence intervals (as pictured):Abstract Figuredanielevanslab.shinyapps.io/COVID_mortality/

signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases.

We assembled an ancestrally diverse collection of genome-wide association studies of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent). We identified 277 loci at genome-wide significance (p-8), including 237 attaining a more stringent trans-ancestry threshold (p-9), which were delineated to 338 distinct association signals. Trans-ancestry meta-regression offered substantial enhancements to fine-mapping, with 58.6% of associations more precisely localised due to population diversity, and 54.4% of signals resolved to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying foundations for functional investigations. Trans-ancestry genetic risk scores enhanced transferability across diverse populations, providing a step towards more effective clinical translation to improve global health.

BackgroundPolygenic risk scores (PRS) have been developed to predict individual cancer risk and their potential clinical utility is receiving a great deal of attention. However, the degree to which the predictive utility of individual cancer-specific PRS may be augmented or refined by the incorporation of other cancer PRS, non-cancer disease PRS, or the protective effects of health and longevity-associated variants, is largely unexplored.MethodsWe constructed PRS for different cancers from public domain data as well as genetic scores for longevity (‘Polygenic Longevity Scores’ or ‘PLS’) for individuals in the UK Biobank. We then explored the relationships of these multiple PRS and PLS among those with and without various cancers.ResultsWe found statistically significant associations between some PLS and individual cancers, even after accounting for cancer-specific PRS. None of the PLS in their current form had an effect pronounced enough to motivate clinical cancer risk stratification based on its combined use with cancer PRS. A few variants at loci used in the PLS had known associations with Alzheimer’s disease and other diseases.ConclusionUnderlying heterogeneity behind cancer susceptibility in the population at large is not captured by PRS derived from analytical models that only consider marginal associations of individual variants with cancer diagnoses. Our results have implications for the derivation and calculation of PRS and their use in clinical and biomedical research settings.ImpactExtensions of analyses like ours could result in a more refined understanding of cancer biology and how to construct PRS for cancer.

Hypertension (HTN) is a significant risk factor for cardiovascular morbidity and mortality. Metabolic abnormalities, including adverse cholesterol and triglycerides (TG) profiles, are frequent comorbid findings with HTN and contribute to cardiovascular disease. Diuretics, which are used to treat HTN and heart failure, have been associated with worsening of fasting lipid concentrations. Genome-wide meta-analyses with 39,710 European-ancestry (EA) individuals and 9925 African-ancestry (AA) individuals were performed to identify genetic variants that modify the effect of loop or thiazide diuretic use on blood lipid concentrations. Both longitudinal and cross sectional data were used to compute cohort-specific interaction results, which were then combined through meta-analysis in each ancestry. These ancestry-specific results were further combined through trans-ancestry meta-analysis. Analysis of EA data identified two genome-wide significant (p

© 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals, Inc. We aimed to report the first genomewide association study (GWAS) meta-analysis of dual-energy X-ray absorptiometry (DXA)-derived hip shape, which is thought to be related to the risk of both hip osteoarthritis and hip fracture. Ten hip shape modes (HSMs) were derived by statistical shape modeling using SHAPE software, from hip DXA scans in the Avon Longitudinal Study of Parents and Children (ALSPAC; adult females), TwinsUK (mixed sex), Framingham Osteoporosis Study (FOS; mixed), Osteoporotic Fractures in Men study (MrOS), and Study of Osteoporotic Fractures (SOF; females) (total N = 15,934). Associations were adjusted for age, sex, and ancestry. Five genomewide significant (p < 5 × 10−9, adjusted for 10 independent outcomes) single-nucleotide polymorphisms (SNPs) were associated with HSM1, and three SNPs with HSM2. One SNP, in high linkage disequilibrium with rs2158915 associated with HSM1, was associated with HSM5 at genomewide significance. In a look-up of previous GWASs, three of the identified SNPs were associated with hip osteoarthritis, one with hip fracture, and five with height. Seven SNPs were within 200 kb of genes involved in endochondral bone formation, namely SOX9, PTHrP, RUNX1, NKX3-2, FGFR4, DICER1, and HHIP. The SNP adjacent to DICER1 also showed osteoblast cis-regulatory activity of GSC, in which mutations have previously been reported to cause hip dysplasia. For three of the lead SNPs, SNPs in high LD (r2 > 0.5) were identified, which intersected with open chromatin sites as detected by ATAC-seq performed on embryonic mouse proximal femora. In conclusion, we identified eight SNPs independently associated with hip shape, most of which were associated with height and/or mapped close to endochondral bone formation genes, consistent with a contribution of processes involved in limb growth to hip shape and pathological sequelae. These findings raise the possibility that genetic studies of hip shape might help in understanding potential pathways involved in hip osteoarthritis and hip fracture. © 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals, Inc.

Background Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—can identify low-risk individuals who can safely be excluded from a fracture risk screening program. Methods and findings A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed “gSOS”, and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)–based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. Conclusions Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention., Vincenzo Forgetta and colleagues investigate possible utility of genetic information in assessing fracture risk., Author summary Why was this study done? Osteoporosis screening identifies only a small proportion of the screened population to be eligible for intervention. The prediction of heritable risk factors using polygenic risk scores could decrease the number of screened individuals by reassuring those with low genetic risk. We investigated whether the genetic prediction of heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—could be incorporated into an established screening guideline to identify individuals at low risk for osteoporosis. What did the researchers do and find? Using UK Biobank, we developed a polygenic risk score (gSOS) consisting of 21,717 genetic variants that was strongly correlated with SOS (r2 = 23.2%). Using the National Osteoporosis Guideline Group clinical assessment guidelines in 5 validation cohorts, we estimate that reassuring individuals with a high gSOS, rather than doing further assessments, could reduce the number of clinical-risk-factor-based Fracture Risk Assessment Tool (FRAX) tests and bone-density-measurement-based FRAX tests by 37% and 41%, respectively, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention. What do these findings mean? We show that genetic pre-screening could reduce the number of screening tests needed to identify individuals at risk of osteoporotic fractures. Therefore, the potential exists to improve the efficiency of osteoporosis screening programs without large losses in sensitivity or specificity to identify individuals who should receive an intervention. Further translational studies are needed to test the clinical applications of this polygenic risk score; however, our work shows how such scores could be tested in the clinic.

Publisher's version (útgefin grein)., Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity., Alexander von Humboldt-Stiftung

Thiazide diuretics, commonly used antihypertensives, may cause QT interval (QT) prolongation, a risk factor for highly fatal and difficult to predict ventricular arrhythmias. We examined whether common single-nucleotide polymorphisms (SNPs) modified the association between thiazide use and QT or its component parts (QRS interval, JT interval) by performing ancestry-specific, transethnic and cross-phenotype genome-wide analyses of European (66%), African American (15%) and Hispanic (19%) populations (N = 78 199), leveraging longitudinal data, incorporating corrected standard errors to account for underestimation of interaction estimate variances and evaluating evidence for pathway enrichment. Although no loci achieved genome-wide significance (P

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.Author SummaryLarge genetic studies with hundreds of thousands of patients have been successful at finding genetic variants that associate with disease traits in humans. However, smaller-scale studies can often have inadequate power to discover new genetic associations. Here, we use a small genetic study of Obstructive Sleep Apnea (OSA), to introduce a strategy that both helps find genetic associations and proposes biological hypotheses for the mechanisms behind those associations. To achieve this, we use large genetic studies carried out on traits that are related to OSA, and look for genetic variants that affect both OSA in our small study and the trait in question in the large study. By linking two or more traits at select loci, we were able to, among other results, find a locus that affects the expression of a gene in immune cells (DNA primase subunit 1), a marker of thrombotic and inflammatory processes (plateletcrit) and OSA. This results in a novel genetic association to OSA and a corresponding biological hypothesis behind its effect on OSA.

BACKGROUND Subclinical changes on the electrocardiogram are risk factors for cardiovascular mortality. Recognition and knowledge of electrolyte associations in cardiac electrophysiology are based on only in vitro models and observations in patients with severe medical conditions.OBJECTIVES This study sought to investigate associations between serum electrolyte concentrations and changes in cardiac electrophysiology in the general population.METHODS Summary results collected from 153,014 individuals (54.4% women; mean age 55.1 +/- 12.1 years) from 33 studies (of 5 ancestries) were meta-analyzed. Linear regression analyses examining associations between electrolyte concentrations (mmol/l of calcium, potassium, sodium, and magnesium), and electrocardiographic intervals (RR, QT, QRS, JT, and PR intervals) were performed. The study adjusted for potential confounders and also stratified by ancestry, sex, and use of antihypertensive drugs.RESULTS Lower calcium was associated with longer QT intervals (-11.5 ms; 99.75% confidence interval [CI]: -13.7 to -9.3) and JT duration, with sex-specific effects. In contrast, higher magnesium was associated with longer QT intervals (7.2 ms; 99.75% CI: 1.3 to 13.1) and JT. Lower potassium was associated with longer QT intervals (-2.8 ms; 99.75% CI: -3.5 to -2.0), JT, QRS, and PR durations, but all potassium associations were driven by use of antihypertensive drugs. No physiologically relevant associations were observed for sodium or RR intervals.CONCLUSIONS The study identified physiologically relevant associations between electrolytes and electrocardiographic intervals in a large-scale analysis combining cohorts from different settings. The results provide insights for further cardiac electrophysiology research and could potentially influence clinical practice, especially the association between calcium and QT duration, by which calcium levels at the bottom 2% of the population distribution led to clinically relevant QT prolongation by >5 ms. (C) 2019 by the American College of Cardiology Foundation.

BackgroundThe electrocardiographically quantified QRS duration measures ventricular depolarization and conduction. QRS prolongation has been associated with poor heart failure prognosis and cardiovascular mortality, including sudden death. While previous genome-wide association studies (GWAS) have identified 32 QRS SNPs across 26 loci among European, African, and Asian-descent populations, the genetics of QRS among Hispanics/Latinos has not been previously explored.MethodsWe performed a GWAS of QRS duration among Hispanic/Latino ancestry populations (n = 15,124) from four studies using 1000 Genomes imputed genotype data (adjusted for age, sex, global ancestry, clinical and study-specific covariates). Study-specific results were combined using fixed-effects, inverse variance-weighted meta-analysis.ResultsWe identified six loci associated with QRS (PConclusionsOur QRS duration GWAS, the first in Hispanic/Latino populations, identified two new loci, underscoring the utility of extending large scale genomic studies to currently under-examined populations.

We hypothesized that trait associations with genetically mediated gene expression could be used to screen for genes that are good candidates for translational studies of longevity. We compiled a collection of genetically-mediated transcriptome-wide association studies using 33 traits and outcomes from large-scale, publicly-available GWAS meta-analysis results. The traits/outcomes were grouped within eight categories (aging, anthropometric, cardiovascular, inflammation, lung function, metabolic, musculoskeletal, and neurological). To test the utility of this approach, we examined trait associations with the drug target of statins, and we correctly identified known therapeutic effects and adverse events of statins. Specifically addressing the hypothesis, we examined a collection of candidate longevity-associated genes and identified one gene associated with lifespan that appears to also be associated with protection from atrial fibrillation and hearing impairment without being associated with adverse events. This screening approach can be used to prioritize gene targets for longevity translational efforts.

Summary The G allele of the FOXO3 single nucleotide polymorphism (SNP) rs2802292 exhibits a consistently replicated genetic association with longevity in multiple populations worldwide. The aims of this study were to quantify the mortality risk for the longevity-associated genotype and to discover the particular cause(s) of death associated with this allele in older Americans of diverse ancestry. It involved a 17-year prospective cohort study of 3584 older American men of Japanese ancestry from the Honolulu Heart Program cohort, followed by a 17-year prospective replication study of 1595 white and 1056 black elderly individuals from the Health Aging and Body Composition cohort. The relation between FOXO3 genotype and cause-specific mortality was ascertained for major causes of death including coronary heart disease (CHD), cancer, and stroke. Age-adjusted and multivariable Cox proportional hazards models were used to compute hazard ratios (HRs) for all-cause and cause-specific mortality. We found G allele carriers had a combined (Japanese, white, and black populations) risk reduction of 10% for total (all-cause) mortality (HR = 0.90; 95% CI, 0.84–0.95; P = 0.001). This effect size was consistent across populations and mostly contributed by 26% lower risk for CHD death (HR = 0.74; 95% CI, 0.64–0.86; P = 0.00004). No other causes of death made a significant contribution to the survival advantage for G allele carriers. In conclusion, at older age, there is a large risk reduction in mortality for G allele carriers, mostly due to lower CHD mortality. The findings support further research on FOXO3 and FoxO3 protein as potential targets for therapeutic intervention in aging-related diseases, particularly cardiovascular disease.

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.

BackgroundApolipoprotein E is a glycoprotein best known as a mediator and regulator of lipid transport and uptake. The APOE-ε4 allele has long been associated with increased risks of Alzheimer's disease and mortality, but the effect of the less prevalent APOE-ε2 allele on diseases in the elderly and survival remains elusive.MethodsWe aggregated data of 38,537 individuals of European ancestry (mean age 65.5 years; 55.6% women) from six population-based cohort studies (Rotterdam Study, AGES-Reykjavik Study, Cardiovascular Health Study, Health-ABC Study, and the family-based Framingham Heart Study and Long Life Family Study) to determine the association of APOE, and in particular APOE-ε2, with survival in the population.ResultsDuring a mean follow-up of 11.7 years, 17,021 individuals died. Compared with homozygous APOE-ε3 carriers, APOE-ε2 carriers were at lower risk of death (hazard ratio,95% confidence interval: 0.94,0.90-0.99; P = 1.1*10-2), whereas APOE-ε4 carriers were at increased risk of death (HR 1.17,1.12-1.21; P = 2.8*10-16). APOE was associated with mortality risk in a dose-dependent manner, with risk estimates lowest for homozygous APOE-ε2 (HR 0.89,0.74-1.08), and highest for homozygous APOE-ε4 (HR 1.52,1.37-1.70). After censoring for dementia, effect estimates remained similar for APOE-ε2 (HR 0.95,0.90-1.01), but attenuated for APOE-ε4 (HR 1.07,1.01-1.12). Results were broadly similar across cohorts, and did not differ by age or sex. APOE genotype was associated with baseline lipid fractions (e.g. mean difference(95%CI) in LDL(mg/dL) for ε2 versus ε33: -17.1(-18.1-16.0), and ε4 versus ε33: +5.7(4.8;6.5)), but the association between APOE and mortality was unaltered after adjustment for baseline LDL or cardiovascular disease. Given the European ancestry of the study population, results may not apply to other ethnicities.ConclusionCompared with APOE-ε3, APOE-ε2 is associated with prolonged survival, whereas mortality risk is increased for APOE-ε4 carriers. Further collaborative efforts are needed to unravel the role of APOE and in particular APOE-ε2 in health and disease.