Search

Complex trait-associated genetic variation is highly pleiotropic. This extensive pleiotropy implies that multi-phenotype analyses are informative for characterizing genetic associations, as they facilitate the discovery of trait-shared and trait-specific variants and pathways ("genetic factors"). Previous efforts have estimated genetic factors using matrix factorization (MF) applied to numerous GWAS. However, existing methods are susceptible to spurious factors arising from residual confounding due to sample-sharing in biobank GWAS. Furthermore, MF approaches have historically estimated dense factors, loaded on most traits and variants, that are challenging to map onto interpretable biological pathways. To address these shortcomings, we introduce "GWAS latent embeddings accounting for noise and regularization" (GLEANR), a MF method for detection of sparse genetic factors from summary statistics. GLEANR accounts for sample sharing between studies and uses regularization to estimate a data-driven number of interpretable factors. GLEANR is robust to confounding induced by shared samples and improves the replication of genetic factors derived from distinct biobanks. We used GLEANR to evaluate 137 diverse GWAS from the UK Biobank, identifying 58 factors that decompose the genetic architecture of input traits and have distinct signatures of negative selection and degrees of polygenicity. These sparse factors can be interpreted with respect to disease, cell-type, and pathway enrichment. We highlight three such factors capturing platelet measure phenotypes and enriched for disease-relevant markers corresponding to distinct stages of platelet differentiation. Overall, GLEANR is a powerful tool for discovering both trait-specific and trait-shared pathways underlying complex traits from GWAS summary statistics.

The effects of genetic variation on complex traits act mainly through changes in gene regulation. Although many genetic variants have been linked to target genes in cis, the trans-regulatory cascade mediating their effects remains largely uncharacterized. Mapping trans-regulators based on natural genetic variation has been challenging due to small effects, but experimental perturbations offer a complementary approach. Using CRISPR, we knocked out 84 genes in primary CD4 + T cells, targeting inborn error of immunity (IEI) disease transcription factors (TFs) and TFs without immune disease association. We developed a novel gene network inference method called linear latent causal Bayes (LLCB) to estimate the network from perturbation data and observed 211 regulatory connections between genes. We characterized programs affected by the TFs, which we associated with immune genome-wide association study (GWAS) genes, finding that JAK-STAT family members are regulated by KMT2A, an epigenetic regulator. These analyses reveal the trans-regulatory cascades linking GWAS genes to signaling pathways., Competing Interests: Declaration of interests A.M. is a cofounder of Site Tx, Arsenal Biosciences, Spotlight Therapeutics, and Survey Genomics; serves on the boards of directors at Site Tx, Spotlight Therapeutics, and Survey Genomics; is a member of the scientific advisory boards of Site Tx, Arsenal Biosciences, Cellanome, Spotlight Therapeutics, Survey Genomics, NewLimit, Amgen, and Tenaya; owns stock in Arsenal Biosciences, Site Tx, Cellanome, Spotlight Therapeutics, NewLimit, Survey Genomics, Tenaya, and Lightcast; and has received fees from Site Tx, Arsenal Biosciences, Cellanome, Spotlight Therapeutics, NewLimit, Gilead, Pfizer, 23andMe, PACT Pharma, Juno Therapeutics, Tenaya, Lightcast, Trizell, Vertex, Merck, Amgen, Genentech, GLG, ClearView Healthcare, AlphaSights, Rupert Case Management, Bernstein, and ALDA. A.M. is an investor in and informal advisor to Offline Ventures and a client of EPIQ. The Marson laboratory has received research support from the Parker Institute for Cancer Immunotherapy, the Emerson Collective, Arc Institute, Juno Therapeutics, Epinomics, Sanofi, GlaxoSmithKline, Gilead, and Anthem and reagents from Genscript and Illumina. J.W.F. was a consultant for NewLimit, is an employee of Genentech, and has equity in Roche. A.B. is a stockholder in Alphabet, Inc., and a consultant for Third Rock Ventures. J.S.W. was a consultant to Spiral Genetics., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer novel insights into downstream clinical consequences. Here, we explore such patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 ancestrally diverse participants (3,881 with CHIP) from NHLBI TOPMed and UK Biobank with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2,917 proteins by Olink in UK Biobank), we identified 32 and 345 unique proteins from TOPMed and UK Biobank, respectively, associated with the most prevalent driver genes ( DNMT3A , TET2 , and ASXL1 ). These associations showed substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic Tet2 -/- vs wild-type mice validation, disentangled causal proteomic perturbations from TET2 CHIP. Lastly, we identified plasma proteins shared between CHIP and CAD.

Expression forecasting methods use machine learning models to predict how a cell will alter its transcriptome upon perturbation. Such methods are enticing because they promise to answer pressing questions in fields ranging from developmental genetics to cell fate engineering and because they are a fast, cheap, and accessible complement to the corresponding experiments. However, the absolute and relative accuracy of these methods is poorly characterized, limiting their informed use, their improvement, and the interpretation of their predictions. To address these issues, we created a benchmarking platform that combines a panel of 11 large-scale perturbation datasets with an expression forecasting software engine that encompasses or interfaces to a wide variety of methods. We used our platform to systematically assess methods, parameters, and sources of auxiliary data, finding that performance strongly depends on the choice of metric, and especially for simple metrics like mean squared error, it is uncommon for expression forecasting methods to out-perform simple baselines. Our platform will serve as a resource to improve methods and to identify contexts in which expression forecasting can succeed.

Clonal hematopoiesis (CH) is defined by the expansion of a lineage of genetically identical cells in blood. Genetic lesions that confer a fitness advantage, such as point mutations or mosaic chromosomal alterations (mCAs) in genes associated with hematologic malignancy, are frequent mediators of CH. However, recent analyses of both single cell-derived colonies of hematopoietic cells and population sequencing cohorts have revealed CH frequently occurs in the absence of known driver genetic lesions. To characterize CH without known driver genetic lesions, we used 51,399 deeply sequenced whole genomes from the NHLBI TOPMed sequencing initiative to perform simultaneous germline and somatic mutation analyses among individuals without leukemogenic point mutations (LPM), which we term CH-LPMneg. We quantified CH by estimating the total mutation burden. Because estimating somatic mutation burden without a paired-tissue sample is challenging, we developed a novel statistical method, the Genomic and Epigenomic informed Mutation (GEM) rate, that uses external genomic and epigenomic data sources to distinguish artifactual signals from true somatic mutations. We performed a genome-wide association study of GEM to discover the germline determinants of CH-LPMneg. After fine-mapping and variant-to-gene analyses, we identified seven genes associated with CH-LPMneg ( TCL1A, TERT, SMC4, NRIP1, PRDM16 , MSRA , SCARB1 ), and one locus associated with a sex-associated mutation pathway ( SRGAP2C) . We performed a secondary analysis excluding individuals with mCAs, finding that the genetic architecture was largely unaffected by their inclusion. Functional analyses of SMC4 and NRIP1 implicated altered HSC self-renewal and proliferation as the primary mediator of mutation burden in blood. We then performed comprehensive multi-tissue transcriptomic analyses, finding that the expression levels of 404 genes are associated with GEM. Finally, we performed phenotypic association meta-analyses across four cohorts, finding that GEM is associated with increased white blood cell count and increased risk for incident peripheral artery disease, but is not significantly associated with incident stroke or coronary disease events. Overall, we develop GEM for quantifying mutation burden from WGS without a paired-tissue sample and use GEM to discover the genetic, genomic, and phenotypic correlates of CH-LPMneg., Competing Interests: Competing Interests Declaration L.M.R. is a consultant for the TOPMed Administrative Coordinating Center (through Westat). B.M.P. serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. J.Y. reports grant support from Bayer. M.C. reports grant support from Bayer and GSK, Consulting and speaking fees from Illumina and AstraZeneca. A.G.B., P.N, and S.J. are cofounders, equity holders, and on the scientific advisory board of TenSixteen Bio. G.R.A. is an employee of Regeneron Pharmaceuticals and receives salary, stock and stock options as compensation.

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation., (© 2024. The Author(s).)

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R 2  = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT., (© 2024. The Author(s).)

Clonal hematopoiesis of indeterminate potential (CHIP) is a premalignant expansion of mutated hematopoietic stem cells. As CHIP-associated mutations are known to alter the development and function of myeloid cells, we hypothesized that CHIP may also be associated with the risk of Alzheimer's disease (AD), a disease in which brain-resident myeloid cells are thought to have a major role. To perform association tests between CHIP and AD dementia, we analyzed blood DNA sequencing data from 1,362 individuals with AD and 4,368 individuals without AD. Individuals with CHIP had a lower risk of AD dementia (meta-analysis odds ratio (OR) = 0.64, P = 3.8 × 10 -5 ), and Mendelian randomization analyses supported a potential causal association. We observed that the same mutations found in blood were also detected in microglia-enriched fraction of the brain in seven of eight CHIP carriers. Single-nucleus chromatin accessibility profiling of brain-derived nuclei in six CHIP carriers revealed that the mutated cells comprised a large proportion of the microglial pool in the samples examined. While additional studies are required to validate the mechanistic findings, these results suggest that CHIP may have a role in attenuating the risk of AD., (© 2023. The Author(s).)

Clonal hematopoiesis of indeterminate potential (CHIP) is a common form of age-related somatic mosaicism that is associated with significant morbidity and mortality. CHIP mutations can be identified in peripheral blood samples that are sequenced using approaches that cover the whole genome, the whole exome, or targeted genetic regions; however, differentiating true CHIP mutations from sequencing artifacts and germ line variants is a considerable bioinformatic challenge. We present a stepwise method that combines filtering based on sequencing metrics, variant annotation, and population-based associations to increase the accuracy of CHIP calls. We apply this approach to ascertain CHIP in ∼550 000 individuals in the UK Biobank complete whole exome cohort and the All of Us Research Program initial whole genome release cohort. CHIP ascertainment on this scale unmasks recurrent artifactual variants and highlights the importance of specialized filtering approaches for several genes, including TET2 and ASXL1. We show how small changes in filtering parameters can considerably increase CHIP misclassification and reduce the effect size of epidemiological associations. Our high-fidelity call set refines previous population-based associations of CHIP with incident outcomes. For example, the annualized incidence of myeloid malignancy in individuals with small CHIP clones is 0.03% per year, which increases to 0.5% per year among individuals with very large CHIP clones. We also find a significantly lower prevalence of CHIP in individuals of self-reported Latino or Hispanic ethnicity in All of Us, highlighting the importance of including diverse populations. The standardization of CHIP calling will increase the fidelity of CHIP epidemiological work and is required for clinical CHIP diagnostic assays., (© 2023 by The American Society of Hematology.)

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

Chronic liver disease is a major public health burden worldwide 1 . Although different aetiologies and mechanisms of liver injury exist, progression of chronic liver disease follows a common pathway of liver inflammation, injury and fibrosis 2 . Here we examined the association between clonal haematopoiesis of indeterminate potential (CHIP) and chronic liver disease in 214,563 individuals from 4 independent cohorts with whole-exome sequencing data (Framingham Heart Study, Atherosclerosis Risk in Communities Study, UK Biobank and Mass General Brigham Biobank). CHIP was associated with an increased risk of prevalent and incident chronic liver disease (odds ratio = 2.01, 95% confidence interval (95% CI) [1.46, 2.79]; P < 0.001). Individuals with CHIP were more likely to demonstrate liver inflammation and fibrosis detectable by magnetic resonance imaging compared to those without CHIP (odds ratio = 1.74, 95% CI [1.16, 2.60]; P = 0.007). To assess potential causality, Mendelian randomization analyses showed that genetic predisposition to CHIP was associated with a greater risk of chronic liver disease (odds ratio = 2.37, 95% CI [1.57, 3.6]; P < 0.001). In a dietary model of non-alcoholic steatohepatitis, mice transplanted with Tet2-deficient haematopoietic cells demonstrated more severe liver inflammation and fibrosis. These effects were mediated by the NLRP3 inflammasome and increased levels of expression of downstream inflammatory cytokines in Tet2-deficient macrophages. In summary, clonal haematopoiesis is associated with an elevated risk of liver inflammation and chronic liver disease progression through an aberrant inflammatory response., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Mutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis 1 . These lesions are precursors for blood cancers 2-6 , but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but this effect was not seen in clones with driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Age-related changes to the genome-wide DNA methylation (DNAm) pattern observed in blood are well-documented. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by the age-related acquisition and expansion of leukemogenic mutations in hematopoietic stem cells (HSCs), is associated with blood cancer and coronary artery disease (CAD). Epigenetic regulators DNMT3A and TET2 are the two most frequently mutated CHIP genes. Here, we present results from an epigenome-wide association study for CHIP in 582 Cardiovascular Health Study (CHS) participants, with replication in 2655 Atherosclerosis Risk in Communities (ARIC) Study participants. We show that DNMT3A and TET2 CHIP have distinct and directionally opposing genome-wide DNAm association patterns consistent with their regulatory roles, albeit both promoting self-renewal of HSCs. Mendelian randomization analyses indicate that a subset of DNAm alterations associated with these two leading CHIP genes may promote the risk for CAD., (© 2022. The Author(s).)

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program ( n = 63,302) and UK Biobank ( n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

BACKGROUNDCurative gene therapies for sickle cell disease (SCD) are currently undergoing clinical evaluation. The occurrence of myeloid malignancies in these trials has prompted safety concerns. Individuals with SCD are predisposed to myeloid malignancies, but the underlying causes remain undefined. Clonal hematopoiesis (CH) is a premalignant condition that also confers significant predisposition to myeloid cancers. While it has been speculated that CH may play a role in SCD-associated cancer predisposition, limited data addressing this issue have been reported.METHODSHere, we leveraged 74,190 whole-genome sequences to robustly study CH in SCD. Somatic mutation calling methods were used to assess CH in all samples and comparisons between individuals with and without SCD were performed.RESULTSWhile we had sufficient power to detect a greater than 2-fold increased rate of CH, we found no detectable variation in rate or clone properties between individuals affected by SCD and controls. The rate of CH in individuals with SCD was unaltered by hydroxyurea use.CONCLUSIONSWe did not observe an increased risk for acquiring detectable CH in SCD, at least as measured by whole-genome sequencing. These results should help guide ongoing efforts and further studies that seek to better define the risk factors underlying myeloid malignancy predisposition in SCD and help ensure that curative therapies can be more safely applied.FUNDINGNew York Stem Cell Foundation and the NIH.

Introduction The purpose of our study is to determine in-hospital outcomes of acute myocardial infarction in patients with hematological malignancies and their subtypes. Method Patient data were obtained from the nationwide inpatient sample (NIS) database between the years 2009-2014. Patients with hematological cancer subtypes and acute MI (non-ST segment elevation myocardial infarction and ST-segment elevation myocardial infarction (NSTEMI/STEMI) were identified using validated international classification of diseases (ninth revision) and clinical modification (ICD-9-CM) codes. Statistical analysis using the chi-square test was performed to determine the hospital outcomes of acute MI in patients with hematological cancers and subtypes. Results The prevalence of acute myocardial infarction was 2.4% in patients with hematological neoplasms (N=3,027,800). Amongst the subtypes of blood cancers, the highest prevalence of acute MI was seen in lymphocytic leukemia (2.9%). The mortality of MI in patients with hematological malignancies was 16.8% vs 8.8% in patients with non-hematological malignancies, in-hospital costs were $25469 ± 36763 vs. $20534 ± 24767, and length of in-hospital stay was 8.3 ± 10 vs 6.3 ± 7.8 days. Amongst the hematological cancer subtypes, the highest mortality of acute MI was found in myeloid leukemia (23%) followed by multiple myeloma (MM) (17.9%), lymphocytic leukemia (15.9%), and lymphoma (14.4%). The length of stay and hospitalization cost was highest for myeloid leukemia, followed by MM, lymphocytic leukemia, and lymphoma. Conclusion This study showed that acute MI in patients with hematological malignancies has higher in-hospital mortality, length of stay, and cost. Amongst the blood neoplasm subtypes the highest mortality, length of hospital stay, and hospitalization cost were found in myeloid leukemia., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2022, Khan et al.)

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value <5×10 -9 ) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 ( STN1 ). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B ( SNM1B ) and PARN . In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes., Competing Interests: Declaration of Interests: The authors declare the following competing interests: J.C.C. has received research materials from GlaxoSmithKline and Merck (inhaled steroids) and Pharmavite (vitamin D and placebo capsules) to provide medications free of cost to participants in NIH-funded studies, unrelated to the current work. B.I.F. is a consultant for AstraZeneca Pharmaceuticals and RenalytixAI L.W. is on the advisory board for GlaxoSmithKline and receives grant funding from NIAID, NHLBI, and NIDDK, NIH I.V.Y. is a consultant for ElevenP15 S.A. receives equity and salary from 23andMe, Inc. M.H.C. receives grant support from GlaxoSmithKline S.T.W. receives royalties from UpToDate E.K.S. received grant support from GlaxoSmithKline and Bayer in the past three years. B.M.P. serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. F.D.M. is supported by grants from NIH/NHLBI (HL139054,HL091889,HL132523,HL130045,HL098112,HL056177), the NIH/NIEHS (ES006614), the NIH/NIAID (AI126614), and the NIH/ Office of Director (OD023282). Vifor Pharmaceuticals provided medicine and additional funding to support recruitment for HL130045. Dr. Martinez is a council member for the Council for the Developing Child. P.T.E. is supported by a grant from Bayer AG to the Broad Institute focused on the genetics and therapeutics of cardiovascular diseases. Dr. Ellinor has also served on advisory boards or consulted for Bayer AG, Quest Diagnostics, and Novartis. K.C.B. receives royalties from UpToDate G.A. is an employee of Regeneron Pharmaceuticals and owns stock and stock options for Regeneron Pharmaceuticals. A.M. is an employee of Regeneron Pharmaceuticals and owns stock and stock options for Regeneron Pharmaceuticals. A.B. is a consultant for Third Rock Ventures, LLC and holds stock in Google, Inc. D.A.S. is the founder and chief scientific officer of Eleven P15, a company focused on the early diagnosis and treatment of pulmonary fibrosis

Clonal hematopoiesis results from somatic mutations in cancer driver genes in hematopoietic stem cells. We sought to identify novel drivers of clonal expansion using an unbiased analysis of sequencing data from 84,683 persons and identified common mutations in the 5-methylcytosine reader, ZBTB33 , as well as in YLPM1 , SRCAP , and ZNF318 . We also identified these mutations at low frequency in myelodysplastic syndrome patients. Zbtb33 edited mouse hematopoietic stem and progenitor cells exhibited a competitive advantage in vivo and increased genome-wide intron retention. ZBTB33 mutations potentially link DNA methylation and RNA splicing, the two most commonly mutated pathways in clonal hematopoiesis and MDS., Competing Interests: Conflict of Interest statement: B.L.E. has received research funding from Celgene and Deerfield. He has received consulting fees from GRAIL, and he serves on the scientific advisory boards for and holds equity in Skyhawk Therapeutics and Exo Therapeutics. S.J. has received consulting fees from GRAIL, Novartis, and Roche Genentech. M.H.C. has received grant support from GSK and Bayer and speaking and consulting fees from AstraZeneca and Illumina.

Clonal hematopoiesis of indeterminate potential (CHIP) is a common precursor state for blood cancers that most frequently occurs due to mutations in the DNA-methylation modifying enzymes DNMT3A or TET2. We used DNA-methylation array and whole-genome sequencing data from four cohorts together comprising 5522 persons to study the association between CHIP, epigenetic clocks, and health outcomes. CHIP was strongly associated with epigenetic age acceleration, defined as the residual after regressing epigenetic clock age on chronological age, in several clocks, ranging from 1.31 years (GrimAge, p < 8.6 × 10 -7 ) to 3.08 years (EEAA, p < 3.7 × 10 -18 ). Mutations in most CHIP genes except DNA-damage response genes were associated with increases in several measures of age acceleration. CHIP carriers with mutations in multiple genes had the largest increases in age acceleration and decrease in estimated telomere length. Finally, we found that ~40% of CHIP carriers had acceleration >0 in both Hannum and GrimAge (referred to as AgeAccelHG+). This group was at high risk of all-cause mortality (hazard ratio 2.90, p < 4.1 × 10 -8 ) and coronary heart disease (CHD) (hazard ratio 3.24, p < 9.3 × 10 -6 ) compared to those who were CHIP-/AgeAccelHG-. In contrast, the other ~60% of CHIP carriers who were AgeAccelHG- were not at increased risk of these outcomes. In summary, CHIP is strongly linked to age acceleration in multiple clocks, and the combination of CHIP and epigenetic aging may be used to identify a population at high risk for adverse outcomes and who may be a target for clinical interventions., (© 2021 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.)

Purpose: We hypothesized patients implanted with ILRs for cryptogenic stroke in "real life" clinical practice will show an AF detection rate comparable to prior clinical studies, and that clinical or imaging features may help to identify those at higher risk of AF detection., Methods: A retrospective chart review was conducted of all patients who presented with cryptogenic stroke and received an ILR at an academic medical center from 2015 to 2017 with an active inpatient stroke service. The electronic health record and remote monitoring were used to identify occurrence of AF., Results: A total of 178 patients who received ILRs for cryptogenic stroke were included. Overall, after a thorough evaluation for other etiologies of stroke, 35 (19.6%) were found to have AF detected. Mean follow-up was 365 days with a median time to detection of 131 days. Advanced age (p = 0.001), diastolic dysfunction on echo (p = 0.03), as well as ECG findings of premature atrial contractions (PACs) and p wave dispersion (PWD) > 40 ms were found to be predictive of AF detection (p = 0.04, p < 0.001, respectively). On multiple regression analysis, the only independent predictor of AF detection was PWD > 40 ms., Conclusion: After a thorough evaluation to exclude other etiologies for stroke, approximately 20% of patients of our cryptogenic stroke population were found to have AF with ILR surveillance. Advanced age, diastolic dysfunction, as well as ECG findings of PACs and increased PWD may help to predict those at higher risk of AF detection, while PWD was the only independent predictor. This has important clinical implications, as better prediction of AF may help identify those at highest risk and might subsequently aid in guiding therapy., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background Presence of clonal hematopoiesis of indeterminate potential (CHIP) is associated with a higher risk of atherosclerotic cardiovascular disease, cancer, and mortality. The relationship between a healthy lifestyle and CHIP is unknown. Methods and Results This analysis included 8709 postmenopausal women (mean age, 66.5 years) enrolled in the WHI (Women's Health Initiative), free of cancer or cardiovascular disease, with deep-coverage whole genome sequencing data available. Information on lifestyle factors (body mass index, smoking, physical activity, and diet quality) was obtained, and a healthy lifestyle score was created on the basis of healthy criteria met (0 point [least healthy] to 4 points [most healthy]). CHIP was derived on the basis of a prespecified list of leukemogenic driver mutations. The prevalence of CHIP was 8.6%. A higher healthy lifestyle score was not associated with CHIP (multivariable-adjusted odds ratio [OR] [95% CI], 0.99 [0.80-1.23] and 1.13 [0.93-1.37]) for the upper (3 or 4 points) and middle category (2 points), respectively, versus referent (0 or 1 point). Across score components, a normal and overweight body mass index compared with obese was significantly associated with a lower odds for CHIP (OR, 0.71 [95% CI, 0.57-0.88] and 0.83 [95% CI, 0.68-1.01], respectively; P -trend 0.0015). Having never smoked compared with being a current smoker tended to be associated with lower odds for CHIP. Conclusions A healthy lifestyle, based on a composite score, was not related to CHIP among postmenopausal women. However, across individual lifestyle factors, having a normal body mass index was strongly associated with a lower prevalence of CHIP. These findings support the idea that certain healthy lifestyle factors are associated with a lower frequency of CHIP.

Phenotypes extracted from Electronic Health Records (EHRs) are increasingly prevalent in genetic studies. EHRs contain hundreds of distinct clinical laboratory test results, providing a trove of health data beyond diagnoses. Such lab data is complex and lacks a ubiquitous coding scheme, making it more challenging than diagnosis data. Here we describe the first large-scale cross-health system genome-wide association study (GWAS) of EHR-based quantitative laboratory-derived phenotypes. We meta-analyzed 70 lab traits matched between the BioVU cohort from the Vanderbilt University Health System and the Michigan Genomics Initiative (MGI) cohort from Michigan Medicine. We show high replication of known association for these traits, validating EHR-based measurements as high-quality phenotypes for genetic analysis. Notably, our analysis provides the first replication for 699 previous GWAS associations across 46 different traits. We discovered 31 novel associations at genome-wide significance for 22 distinct traits, including the first reported associations for two lab-based traits. We replicated 22 of these novel associations in an independent tranche of BioVU samples. The summary statistics for all association tests are freely available to benefit other researchers. Finally, we performed mirrored analyses in BioVU and MGI to assess competing analytic practices for EHR lab traits. We find that using the mean of all available lab measurements provides a robust summary value, but alternate summarizations can improve power in certain circumstances. This study provides a proof-of-principle for cross health system GWAS and is a framework for future studies of quantitative EHR lab traits., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: G.R.A. is an employee of Regeneron Pharmaceuticals. He owns stock and stock options for Regeneron Pharmaceuticals. L.A.B and J.C.D receive royalty payments from Nashville Biosciences, a Vanderbilt University Medical Center owned entity.

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown 1 . The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer 2-4 and coronary heart disease 5 -this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP) 6 . Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

Background: Cardiovascular diseases are the leading cause of death in the USA. Statin therapy reduces cardiovascular events significantly. Cognitive impairment has been reported with statin therapy but there is a lack of consensus. We analyzed the cognitive functions of adult patients who were on moderate-intensity statin therapy (MIST) or high-intensity statin therapy (HIST)., Methods: A total of 213 patients underwent cognitive assessment testing. Cognitive function scores were correlated with the durations of statin therapy, age, and level of education by using Pearson correlation. Independent t -test was used to compare the mean cognitive function score to the gender, race, type of statin therapy, and comorbid conditions., Results: Mean age of all the patients was 55.4 years. Majority of the patients (66.2%) were on MIST while the rest (33.8%) were on HIST. Cognitive impairment was observed in 17.8% of the studied patients. A total of 41.7% of the patients in the HIST group and 5.7% in the MIST group had cognitive impairment (P < 0.001). There was no correlation between cognitive function score and age (r = -0.106), weakly positive correlation between the level of education and cognitive function score (r = 0.252), and weakly negative correlation between the duration of statin therapy and cognitive function score (r = -0.283). In the group of patients on HIST with cognitive impairment, the proportion of patients on atorvastatin 40 - 80 mg was significantly higher than the proportion of patients on rosuvastatin 20 - 40 mg (66.7% vs. 33.3%; P < 0.05). In the group of patients on MIST with cognitive impairment, atorvastatin 10 - 20 mg was the most commonly used statin therapy (50%), followed by rosuvastatin 10 mg (25%), simvastatin 20 - 40 mg (12.5%) and pravastatin 40 - 80 mg (12.5%)., Conclusions: We found a significantly higher association of cognitive impairment in patients who were on MIST or HIST compared to the general population. We found no correlation between cognitive function score and age, weakly positive correlation between the level of education and cognitive function score, and weakly negative correlation between the duration of statin therapy and cognitive function score. HIST was associated with a higher frequency of cognitive impairment compared to the MIST., Competing Interests: None to declare., (Copyright 2020, Roy et al.)

A 71-year-old woman with metastatic squamous cell carcinoma of the lung and insulin-dependent type 2 diabetes mellitus presented with a necrotic lesion on her lower abdomen. Further history revealed that this was the site of repeat insulin injections with reuse of the same needles. On investigation, biopsy of the site was positive for broad, aseptate, right-angle branching fungal hyphae consistent with mucormycosis. Studies have shown that insulin needle reuse is a common practice among diabetics for several reasons, including cost and convenience. While the current American Diabetes Association guidelines suggest that this is an acceptable practice among the general population of diabetics, they advise against it in patients who are actively ill or immunocompromised. Discussion about insulin needle reuse should be of utmost importance among providers and their diabetic patients, especially for patients who are immunocompromised., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Array genotyping is a cost-effective and widely used tool that enables assessment of up to millions of genetic markers in hundreds of thousands of individuals. Genotyping array data are typically highly accurate but sensitive to mixing of DNA samples from multiple individuals before or during genotyping. Contaminated samples can lead to genotyping errors and consequently cause false positive signals or reduce power of association analyses. Here, we propose a new method to identify contaminated samples and the sources of contamination within a genotyping batch. Through analysis of array intensity and genotype data from intentionally mixed samples and 22,366 samples of the Michigan Genomics Initiative, an ongoing biobank-based study, we show that our method can reliably estimate contamination. We also show that identifying sources of contamination can implicate problematic sample processing steps and guide process improvements. Compared to existing methods, our approach can estimate the proportion of contaminating DNA more accurately, eliminate the need for external databases of allele frequencies, and provide contamination estimates that are more robust to the ancestral origin of the contaminating sample., (© 2019 Wiley Periodicals, Inc.)

The power of genetic association analyses can be increased by jointly meta-analyzing multiple correlated phenotypes. Here, we develop a meta-analysis framework, Meta-MultiSKAT, that uses summary statistics to test for association between multiple continuous phenotypes and variants in a region of interest. Our approach models the heterogeneity of effects between studies through a kernel matrix and performs a variance component test for association. Using a genotype kernel, our approach can test for rare-variants and the combined effects of both common and rare-variants. To achieve robust power, within Meta-MultiSKAT, we developed fast and accurate omnibus tests combining different models of genetic effects, functional genomic annotations, multiple correlated phenotypes, and heterogeneity across studies. In addition, Meta-MultiSKAT accommodates situations where studies do not share exactly the same set of phenotypes or have differing correlation patterns among the phenotypes. Simulation studies confirm that Meta-MultiSKAT can maintain the type-I error rate at the exome-wide level of 2.5 × 10 -6 . Further simulations under different models of association show that Meta-MultiSKAT can improve the power of detection from 23% to 38% on average over single phenotype-based meta-analysis approaches. We demonstrate the utility and improved power of Meta-MultiSKAT in the meta-analyses of four white blood cell subtype traits from the Michigan Genomics Initiative (MGI) and SardiNIA studies., (© 2019 Wiley Periodicals, Inc.)

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

Background: Atherosclerotic cardiovascular diseases are the leading cause of death in the United States. A reduction in cholesterol with 3-hydroxy-3-methyl-glutaryl-CoA reductase inhibitors (statin) significantly reduces mortality and morbidity. Statins may be associated with cognitive impairment or dementia. Our aim was to study the association of cognitive impairment or dementia in patients who were on a statin., Methods: Electronic medical records of 3,500 adult patients in our suburban internal medicine office were reviewed., Results: There were 720 (20.6%) patients in the statin treatment group. Dementia or cognitive impairment was an associated comorbid condition in 7.9% patients in the statin treatment group compared to 3.1% patients in the non-statin group (P < 0.001). Analysis of all of the patients with cognitive impairment or dementia showed that among the age ranges of 51 years through 100 years, the patients in the statin treatment group had a higher prevalence of cognitive impairment or dementia compared to the non-statin group. In the statin treatment group, we found significantly higher prevalence of hyperlipidemia (86.3%), hypertension (69.6%), diabetes mellitus (36.0%), osteoarthritis (31.5%), coronary artery disease (26.1%), hypothyroidism (21.5%) and depression (19.3%) compared to the non-statin group (P < 0.001). About 39.9% of the patients with dementia or cognitive impairment were on statin therapy compared to 18.9% patients who had no dementia or cognitive impairment and were on statin therapy (P < 0.001). Among the patients with cognitive deficit or dementia in the statin treatment group, the majority of the patients were either on atorvastatin (43.9%) or simvastatin (35.1%), followed by rosuvastatin (12.2%) and pravastatin (8.8%). We found greater odds of dementia or cognitive impairment with each year increase in age (1.3 times), in women (2.2 times), African American race (2.7 times), non-consumption of moderate amount of alcohol (two times), diabetes mellitus (1.6 times), hypothyroidism (1.7 times), cerebrovascular accident (3.2 times), and other rheumatological diseases (1.8 times)., Conclusions: The association of dementia or cognitive impairment was significantly higher in the patients who were on statin therapy compared to the patients who were not on a statin.