Multiancestry Genome-Wide Association Study of Aortic Stenosis Identifies Multiple Novel Loci in the Million Veteran Program.

BACKGROUND: Calcific aortic stenosis (CAS) is the most common valvular heart disease in older adults and has no effective preventive therapies. Genome-wide association studies (GWAS) can identify genes influencing disease and may help prioritize therapeutic targets for CAS. METHODS: We performed a GWAS and gene association study of 14 451 patients with CAS and 398 544 controls in the Million Veteran Program. Replication was performed in the Million Veteran Program, Penn Medicine Biobank, Mass General Brigham Biobank, BioVU, and BioMe, totaling 12 889 cases and 348 094 controls. Causal genes were prioritized from genome-wide significant variants using polygenic priority score gene localization, expression quantitative trait locus colocalization, and nearest gene methods. CAS genetic architecture was compared with that of atherosclerotic cardiovascular disease. Causal inference for cardiometabolic biomarkers in CAS was performed using Mendelian randomization and genome-wide significant loci were characterized further through phenome-wide association study. RESULTS: We identified 23 genome-wide significant lead variants in our GWAS representing 17 unique genomic regions. Of the 23 lead variants, 14 were significant in replication, representing 11 unique genomic regions. Five replicated genomic regions were previously known risk loci for CAS (PALMD, TEX41, IL6, LPA, FADS) and 6 were novel (CEP85L, FTO, SLMAP, CELSR2, MECOM, CDAN1). Two novel lead variants were associated in non-White individuals (P<0.05): rs12740374 (CELSR2) in Black and Hispanic individuals and rs1522387 (SLMAP) in Black individuals. Of the 14 replicated lead variants, only 2 (rs10455872 [LPA], rs12740374 [CELSR2]) were also significant in atherosclerotic cardiovascular disease GWAS. In Mendelian randomization, lipoprotein(a) and low-density lipoprotein cholesterol were both associated with CAS, but the association between low-density lipoprotein cholesterol and CAS was attenuated when adjusting for lipoprotein(a). Phenome-wide association study highlighted varying degrees of pleiotropy, including between CAS and obesity at the FTO locus. However, the FTO locus remained associated with CAS after adjusting for body mass index and maintained a significant independent effect on CAS in mediation analysis. CONCLUSIONS: We performed a multiancestry GWAS in CAS and identified 6 novel genomic regions in the disease. Secondary analyses highlighted the roles of lipid metabolism, inflammation, cellular senescence, and adiposity in the pathobiology of CAS and clarified the shared and differential genetic architectures of CAS with atherosclerotic cardiovascular diseases.

Common Ancestry-Specific Ion Channel Variants Predispose to Drug-Induced Arrhythmias.

BACKGROUND: Multiple reports associate the cardiac sodium channel gene (SCN5A) variants S1103Y and R1193Q with type 3 congenital long QT syndrome and drug-induced long QT syndrome. These variants are too common in ancestral populations to be highly arrhythmogenic at baseline, however: S1103Y allele frequency is 8.1% in African Americans and R1193Q 6.1% in East Asians. R1193Q is known to increase late sodium current (INa-L) in cardiomyocytes derived from induced pluripotent stem cells but the role of these variants in modulating repolarization remains poorly understood. METHODS: We determined the effect of S1103Y on QT intervals among African-American participants in a large electronic health record. Using cardiomyocytes derived from induced pluripotent stem cells carrying naturally occurring or genome-edited variants, we studied action potential durations (APDs) at baseline and after challenge with the repolarizing potassium current (IKr) blocker dofetilide and INa-L and IKr at baseline. RESULTS: In 1479 African-American participants with no confounding medications or diagnoses of heart disease, QT intervals in S1103Y carriers was no different from that in noncarriers. Baseline APD was no different in cells expressing the Y allele (SY, YY cells) compared with isogenic cells with the reference allele (SS cells). However, INa-L was increased in SY and YY cells and the INa-L blocker GS967 shortened APD in SY/YY but not SS cells (P<0.001). IKr was increased almost 2-fold in SY/YY cells compared with SS cells (tail current: 0.66±0.1 versus 1.2±0.1 pA/pF; P<0.001). Dofetilide challenge prolonged APD at much lower concentrations in SY (4.1 nmol/L [interquartile range, 1.5-9.3]; n=11) and YY (4.2 nmol/L [1.7-5.0]; n=5) than in SS cells (249 nmol/L [22.3-2905]; n=14; P<0.001 and P<0.01, respectively) and elicited afterdepolarizations in 8/16 SY/YY cells but only in 1/14 SS cells. R1193Q cells similarly displayed no difference in baseline APD but increased IKr and increased dofetilide sensitivity. CONCLUSIONS: These common ancestry-specific variants do not affect baseline repolarization, despite generating increased INa-L. We propose that increased IKr serves to maintain normal repolarization but increases the risk of manifest QT prolongation with IKr block in variant carriers. Our findings emphasize the need for inclusion of diverse populations in the study of adverse drug reactions.

Arrhythmia Variant Associations and Reclassifications in the eMERGE-III Sequencing Study.

BACKGROUND: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. METHODS: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record-derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. RESULTS: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. CONCLUSIONS: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier; NCT03394859.

Genome-wide association study reveals novel genetic loci: a new polygenic risk score for mitral valve prolapse.

AIMS: Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder. METHODS AND RESULTS: We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors. CONCLUSION: We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-ß signalling molecules and spectrin ß. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention.

An algorithm to identify cases of pulmonary arterial hypertension from the electronic medical record.

BACKGROUND: Study of pulmonary arterial hypertension (PAH) in claims-based (CB) cohorts may facilitate understanding of disease epidemiology, however previous CB algorithms to identify PAH have had limited test characteristics. We hypothesized that machine learning algorithms (MLA) could accurately identify PAH in an CB cohort. METHODS: ICD-9/10 codes, CPT codes or PAH medications were used to screen an electronic medical record (EMR) for possible PAH. A subset (Development Cohort) was manually reviewed and adjudicated as PAH or "not PAH" and used to train and test MLAs. A second subset (Refinement Cohort) was manually reviewed and combined with the Development Cohort to make The Final Cohort, again divided into training and testing sets, with MLA characteristics defined on test set. The MLA was validated using an independent EMR cohort. RESULTS: 194 PAH and 786 "not PAH" in the Development Cohort trained and tested the initial MLA. In the Final Cohort test set, the final MLA sensitivity was 0.88, specificity was 0.93, positive predictive value was 0.89, and negative predictive value was 0.92. Persistence and strength of PAH medication use and CPT code for right heart catheterization were principal MLA features. Applying the MLA to the EMR cohort using a split cohort internal validation approach, we found 265 additional non-confirmed cases of suspected PAH that exhibited typical PAH demographics, comorbidities, hemodynamics. CONCLUSIONS: We developed and validated a MLA using only CB features that identified PAH in the EMR with strong test characteristics. When deployed across an entire EMR, the MLA identified cases with known features of PAH.

Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease.

Major depressive disorder (MDD) and loneliness are phenotypically and genetically correlated with coronary artery disease (CAD), but whether these associations are explained by pleiotropic genetic variants or shared comorbidities is unclear. To tease apart these scenarios, we first assessed the medical morbidity pattern associated with genetic risk factors for MDD and loneliness by conducting a phenome-wide association study in 18,385 European-ancestry individuals in the Vanderbilt University Medical Center biobank, BioVU. Polygenic scores for MDD and loneliness were developed for each person using previously published meta-GWAS summary statistics, and were tested for association with 882 clinical diagnoses ascertained via billing codes in electronic health records. We discovered strong associations with heart disease diagnoses, and next embarked on targeted analyses of CAD in 3893 cases and 4197 controls. We found odds ratios of 1.11 (95% CI, 1.04-1.18; P 8.43 × 10-4) and 1.13 (95% CI, 1.07-1.20; P 4.51 × 10-6) per 1-SD increase in the polygenic scores for MDD and loneliness, respectively. Results were similar in patients without psychiatric symptoms, and the increased risk persisted in females even after adjusting for multiple conventional risk factors and a polygenic score for CAD. In a final sensitivity analysis, we statistically adjusted for the genetic correlation between MDD and loneliness and re-computed polygenic scores. The polygenic score unique to loneliness remained associated with CAD (OR 1.09, 95% CI 1.03-1.15; P 0.002), while the polygenic score unique to MDD did not (OR 1.00, 95% CI 0.95-1.06; P 0.97). Our replication sample was the Atherosclerosis Risk in Communities (ARIC) cohort of 7197 European-ancestry participants (1598 incident CAD cases). In ARIC, polygenic scores for MDD and loneliness were associated with hazard ratios of 1.07 (95% CI, 0.99-1.14; P = 0.07) and 1.07 (1.01-1.15; P = 0.03), respectively, and we replicated findings from the BioVU sensitivity analyses. We conclude that genetic risk factors for MDD and loneliness act pleiotropically to increase CAD risk in females.

Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort.

From the start of the coronavirus disease 2019 (COVID-19) pandemic, researchers have looked to electronic health record (EHR) data as a way to study possible risk factors and outcomes. To ensure the validity and accuracy of research using these data, investigators need to be confident that the phenotypes they construct are reliable and accurate, reflecting the healthcare settings from which they are ascertained. We developed a COVID-19 registry at a single academic medical center and used data from March 1 to June 5, 2020 to assess differences in population-level characteristics in pandemic and non-pandemic years respectively. Median EHR length, previously shown to impact phenotype performance in type 2 diabetes, was significantly shorter in the SARS-CoV-2 positive group relative to a 2019 influenza tested group (median 3.1 years vs 8.7; Wilcoxon rank sum P = 1.3e-52). Using three phenotyping methods of increasing complexity (billing codes alone and domain-specific algorithms provided by an EHR vendor and clinical experts), common medical comorbidities were abstracted from COVID-19 EHRs, defined by the presence of a positive laboratory test (positive predictive value 100%, recall 93%). After combining performance data across phenotyping methods, we observed significantly lower false negative rates for those records billed for a comprehensive care visit (p = 4e-11) and those with complete demographics data recorded (p = 7e-5). In an early COVID-19 cohort, we found that phenotyping performance of nine common comorbidities was influenced by median EHR length, consistent with previous studies, as well as by data density, which can be measured using portable metrics including CPT codes. Here we present those challenges and potential solutions to creating deeply phenotyped, acute COVID-19 cohorts.

Metabolomics reveals the impact of Type 2 diabetes on local muscle and vascular responses to ischemic stress.

OBJECTIVE: Type 2 diabetes mellitus (T2DM) reduces exercise capacity, but the mechanisms are incompletely understood. We probed the impact of ischemic stress on skeletal muscle metabolite signatures and T2DM-related vascular dysfunction. METHODS: we recruited 38 subjects (18 healthy, 20 T2DM), placed an antecubital intravenous catheter, and performed ipsilateral brachial artery reactivity testing. Blood samples for plasma metabolite profiling were obtained at baseline and immediately upon cuff release after 5 min of ischemia. Brachial artery diameter was measured at baseline and 1 min after cuff release. RESULTS: as expected, flow-mediated vasodilation was attenuated in subjects with T2DM (P<0.01). We confirmed known T2DM-associated baseline differences in plasma metabolites, including homocysteine, dimethylguanidino valeric acid and ß-alanine (all P<0.05). Ischemia-induced metabolite changes that differed between groups included 5-hydroxyindoleacetic acid (healthy: -27%; DM +14%), orotic acid (healthy: +5%; DM -7%), trimethylamine-N-oxide (healthy: -51%; DM +0.2%), and glyoxylic acid (healthy: +19%; DM -6%) (all P<0.05). Levels of serine, betaine, ß-aminoisobutyric acid and anthranilic acid were associated with vessel diameter at baseline, but only in T2DM (all P<0.05). Metabolite responses to ischemia were significantly associated with vasodilation extent, but primarily observed in T2DM, and included enrichment in phospholipid metabolism (P<0.05). CONCLUSIONS: our study highlights impairments in muscle and vascular signaling at rest and during ischemic stress in T2DM. While metabolites change in both healthy and T2DM subjects in response to ischemia, the relationship between muscle metabolism and vascular function is modified in T2DM, suggesting that dysregulated muscle metabolism in T2DM may have direct effects on vascular function.

Effect of Statin Coadministration on the Risk of Daptomycin-Associated Myopathy.

Background: Daptomycin-associated myopathy has been identified in 2%-14% of patients, and rhabdomyolysis is a known adverse effect. Although risk factors for daptomycin-associated myopathy are poorly defined, creatine phosphokinase (CPK) monitoring and temporary discontinuation of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, or "statins," has been recommended. Methods: We conducted a single-center, retrospective, matched case-control risk factor analysis in adult and pediatric patients from 2004 to 2015. Patients in whom myopathy (defined as CPK values above the upper limit of normal) developed during daptomycin treatment were matched 1:1 to no-myopathy controls with at least the same duration of therapy. Risk factors independently associated with myopathy were determined using multivariable conditional logistic regression. Secondary analysis was performed in patients with rhabdomyolysis, defined as CPK values ≥10 times the upper limit of normal. Results: Of 3042 patients reviewed, 128 (4.2%) were identified as having daptomycin-associated myopathy, 25 (0.8%) of whom had rhabdomyolysis; 121 (95%) of the 128 were adults, and the mean duration of therapy before CPK elevation was 16.7 days (range, 1-58 days). In multivariate analysis, deep abscess treatment (odds ratio, 2.80; P = .03), antihistamine coadministration (3.50; P = .03), and statin coadministration (2.60; P = .03) were independent risk factors for myopathy. Obesity (odds ratio, 3.28; P = .03) and statin coadministration (4.67; P = .03) were found to be independent risk factors for rhabdomyolysis, and older age was associated with reduced risk (0.97; P = .05). Conclusions: Statin coadministration with daptomycin was independently associated with myopathy and rhabdomyolysis. This is the first study to provide strong evidence supporting this association. During coadministration, we recommend twice-weekly CPK monitoring and consideration of withholding statins.

Oestrogen inhibition reverses pulmonary arterial hypertension and associated metabolic defects.

Increased oestrogen is a strong epidemiological risk factor for development of pulmonary arterial hypertension (PAH) in patients, associated with metabolic defects. In addition, oestrogens drive penetrance in mice carrying mutations in bone morphogenetic protein receptor type II (BMPR2), the cause of most heritable PAH. The goal of the present study was to determine whether inhibition of oestrogens was effective in the treatment of PAH in these mice.The oestrogen inhibitors fulvestrant and anastrozole were used in a prevention and treatment paradigm in BMPR2 mutant mice, and tamoxifen was used for treatment. In addition, BMPR2 mutant mice were crossed onto oestrogen receptor (ESR)1 and ESR2 knockout backgrounds to assess receptor specificity. Haemodynamic and metabolic outcomes were measured.Oestrogen inhibition both prevented and treated PAH in BMPR2 mutant mice. This was associated with reduction in metabolic defects including oxidised lipid formation, insulin resistance and rescue of peroxisome proliferator-activated receptor-γ and CD36. The effect was mediated primarily through ESR2, but partially through ESR1.Our data suggest that trials of oestrogen inhibition in human PAH are warranted, and may improve pulmonary vascular disease through amelioration of metabolic defects. Although fulvestrant and anastrozole were more effective than tamoxifen, tamoxifen may be useful in premenopausal females, because of a reduced risk of induction of menopause.

Pre-existing Psychiatric Illness is Associated With Increased Risk of Recurrent Takotsubo Cardiomyopathy.

BACKGROUND: The increased prevalence of psychiatric illness among patients with takotsubo cardiomyopathy (TC) has been previously described. OBJECTIVES: We sought to assess the effect of pre-existing psychiatric illness on clinical outcomes following the diagnosis of TC. METHODS: Adults diagnosed with TC at Vanderbilt University Medical Center between 1999 and 2015 were included in the study. Medical records were retrospectively reviewed to identify any pre-existing mood, anxiety, or schizophrenia-spectrum illness before TC presentation. Multivariable logistic regression was used to test for independent association of pre-existing psychiatric illness with 30-day mortality and recurrent TC; Cox proportional hazard analysis was used to evaluate for association with long-term mortality. RESULTS: Among 306 patients diagnosed with TC during the study period, 114 (37%) had a pre-existing psychiatric illness. In all, 43 (14%) and 88 (29%) patients died within 30 days of index diagnosis and as of last medical record review, respectively. Of the 269 who survived their index hospitalization, 19 (7%) had a confirmed recurrent episode of TC. In multivariable analyses, pre-existing psychiatric illness was not associated with increased 30-day (P = 0.320) or long-term (P = 0.621) mortality. Pre-existing psychiatric illness was associated with higher risk of recurrent TC (odds ratio = 7.44, 95% CI: 2.30-24.01, P < 0.001). CONCLUSIONS: Pre-existing psychiatric illness was associated with an increased risk of recurrent TC. No significant association was noted between pre-existing psychiatric illness and survival.

Temperature variability during targeted temperature management is not associated with neurological outcomes following cardiac arrest.

INTRODUCTION: Recent studies on comatose survivors of cardiac arrest undergoing targeted temperature management (TTM) have shown similar outcomes at multiple target temperatures. However, details regarding core temperature variability during TTM and its prognostic implications remain largely unknown. We sought to assess the association between core temperature variability and neurological outcomes in patients undergoing TTM following cardiac arrest. METHODS: We analyzed a prospectively collected cohort of 242 patients treated with TTM following cardiac arrest at a tertiary care hospital between 2007 and 2014. Core temperature variability was defined as the statistical variance (i.e. standard deviation squared) amongst all core temperature recordings during the maintenance phase of TTM. Poor neurological outcome at hospital discharge, defined as a Cerebral Performance Category (CPC) score>2, was the primary outcome. Death prior to hospital discharge was assessed as the secondary outcome. Multivariable logistic regression was used to examine the association between temperature variability and neurological outcome or death at hospital discharge. RESULTS: A poor neurological outcome was observed in 147 (61%) patients and 136 (56%) patients died prior to hospital discharge. In multivariable logistic regression, increased core temperature variability was not associated with increased odds of poor neurological outcomes (OR 0.38, 95% CI 0.11-1.38, p=0.142) or death (OR 0.43, 95% CI 0.12-1.53, p=0.193) at hospital discharge. CONCLUSION: In this study, individual core temperature variability during TTM was not associated with poor neurological outcomes or death at hospital discharge.

Fine Mapping and Identification of BMI Loci in African Americans.

Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.

Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits.

BACKGROUND/AIMS: Present-day limited resources demand DNA and phenotyping alternatives to the traditional prospective population-based epidemiologic collections. METHODS: To accelerate genomic discovery with an emphasis on diverse populations, we--as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study--accessed all non-European American samples (n = 15,863) available in BioVU, the Vanderbilt University biorepository linked to de-identified electronic medical records, for genomic studies as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study. Given previous studies have cautioned against the secondary use of clinically collected data compared with epidemiologically collected data, we present here a characterization of EAGLE BioVU, including the billing and diagnostic (ICD-9) code distributions for adult and pediatric patients as well as comparisons made for select health metrics (body mass index, glucose, HbA1c, HDL-C, LDL-C, and triglycerides) with the population-based National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (NHANES III, n = 7,159; NHANES 1999-2002, n = 7,839). RESULTS: Overall, the distributions of billing and diagnostic codes suggest this clinical sample is a mixture of healthy and sick patients like that expected for a contemporary American population. CONCLUSION: Little bias is observed among health metrics, suggesting this clinical collection is suitable for genomic studies along with traditional epidemiologic cohorts.

Volumetric brain MRI signatures of heart failure with preserved ejection fraction in the setting of dementia.

Heart failure with preserved ejection fraction (HFpEF) is an important, emerging risk factor for dementia, but it is not clear whether HFpEF contributes to a specific pattern of neuroanatomical changes in dementia. A major challenge to studying this is the relative paucity of datasets of patients with dementia, with/without HFpEF, and relevant neuroimaging. We sought to demonstrate the feasibility of using modern data mining tools to create and analyze clinical imaging datasets and identify the neuroanatomical signature of HFpEF-associated dementia. We leveraged the bioinformatics tools at Vanderbilt University Medical Center to identify patients with a diagnosis of dementia with and without comorbid HFpEF using the electronic health record. We identified high resolution, clinically-acquired neuroimaging data on 30 dementia patients with HFpEF (age 76.9 ± 8.12 years, 61% female) as well as 301 age- and sex-matched patients with dementia but without HFpEF to serve as comparators (age 76.2 ± 8.52 years, 60% female). We used automated image processing pipelines to parcellate the brain into 132 structures and quantify their volume. We found six regions with significant atrophy associated with HFpEF: accumbens area, amygdala, posterior insula, anterior orbital gyrus, angular gyrus, and cerebellar white matter. There were no regions with atrophy inversely associated with HFpEF. Patients with dementia and HFpEF have a distinct neuroimaging signature compared to patients with dementia only. Five of the six regions identified in are in the temporo-parietal region of the brain. Future studies should investigate mechanisms of injury associated with cerebrovascular disease leading to subsequent brain atrophy.

Unbiased characterization of atrial fibrillation phenotypic architecture provides insight to genetic liability and clinically relevant outcomes.

Background: Atrial Fibrillation (AF) is a common and clinically heterogeneous arrythmia. Machine learning (ML) algorithms can define data-driven disease subtypes in an unbiased fashion, but whether the AF subgroups defined in this way align with underlying mechanisms, such as high polygenic liability to AF or inflammation, and associate with clinical outcomes is unclear. Methods: We identified individuals with AF in a large biobank linked to electronic health records (EHR) and genome-wide genotyping. The phenotypic architecture in the AF cohort was defined using principal component analysis of 35 expertly curated and uncorrelated clinical features. We applied an unsupervised co-clustering machine learning algorithm to the 35 features to identify distinct phenotypic AF clusters. The clinical inflammatory status of the clusters was defined using measured biomarkers (CRP, ESR, WBC, Neutrophil %, Platelet count, RDW) within 6 months of first AF mention in the EHR. Polygenic risk scores (PRS) for AF and cytokine levels were used to assess genetic liability of clusters to AF and inflammation, respectively. Clinical outcomes were collected from EHR up to the last medical contact. Results: The analysis included 23,271 subjects with AF, of which 6,023 had available genome-wide genotyping. The machine learning algorithm identified 3 phenotypic clusters that were distinguished by increasing prevalence of comorbidities, particularly renal dysfunction, and coronary artery disease. Polygenic liability to AF across clusters was highest in the low comorbidity cluster. Clinically measured inflammatory biomarkers were highest in the high comorbid cluster, while there was no difference between groups in genetically predicted levels of inflammatory biomarkers. Subgroup assignment was associated with multiple clinical outcomes including mortality, stroke, bleeding, and use of cardiac implantable electronic devices after AF diagnosis. Conclusion: Patient subgroups identified by unsupervised clustering were distinguished by comorbidity burden and associated with risk of clinically important outcomes. Polygenic liability to AF across clusters was greatest in the low comorbidity subgroup. Clinical inflammation, as reflected by measured biomarkers, was lowest in the subgroup with lowest comorbidities. However, there were no differences in genetically predicted levels of inflammatory biomarkers, suggesting associations between AF and inflammation is driven by acquired comorbidities rather than genetic predisposition.

LNK/SH2B3 loss of function increases susceptibility to murine and human atrial fibrillation.

AIMS: The lymphocyte adaptor protein (LNK) is a negative regulator of cytokine and growth factor signalling. The rs3184504 variant in SH2B3 reduces LNK function and is linked to cardiovascular, inflammatory, and haematologic disorders, including stroke. In mice, deletion of Lnk causes inflammation and oxidative stress. We hypothesized that Lnk-/- mice are susceptible to atrial fibrillation (AF) and that rs3184504 is associated with AF and AF-related stroke in humans. During inflammation, reactive lipid dicarbonyls are the major components of oxidative injury, and we further hypothesized that these mediators are critical drivers of the AF substrate in Lnk-/- mice. METHODS AND RESULTS: Lnk-/- or wild-type (WT) mice were treated with vehicle or 2-hydroxybenzylamine (2-HOBA), a dicarbonyl scavenger, for 3 months. Compared with WT, Lnk-/- mice displayed increased AF duration that was prevented by 2-HOBA. In the Lnk-/- atria, action potentials were prolonged with reduced transient outward K+ current, increased late Na+ current, and reduced peak Na+ current, pro-arrhythmic effects that were inhibited by 2-HOBA. Mitochondrial dysfunction, especially for Complex I, was evident in Lnk-/- atria, while scavenging lipid dicarbonyls prevented this abnormality. Tumour necrosis factor-α (TNF-α) and interleukin-1 beta (IL-1ß) were elevated in Lnk-/- plasma and atrial tissue, respectively, both of which caused electrical and bioenergetic remodelling in vitro. Inhibition of soluble TNF-α prevented electrical remodelling and AF susceptibility, while IL-1ß inhibition improved mitochondrial respiration but had no effect on AF susceptibility. In a large database of genotyped patients, rs3184504 was associated with AF, as well as AF-related stroke. CONCLUSION: These findings identify a novel role for LNK in the pathophysiology of AF in both experimental mice and humans. Moreover, reactive lipid dicarbonyls are critical to the inflammatory AF substrate in Lnk-/- mice and mediate the pro-arrhythmic effects of pro-inflammatory cytokines, primarily through electrical remodelling.

A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver.

Metabolic dysfunction-associated steatotic liver disease (MASLD) prevalence is increasing in parallel with an obesity pandemic, calling for novel strategies for prevention and treatment. We defined a circulating proteome of human MASLD across ≈7000 proteins in ≈5000 individuals from diverse, at-risk populations across the metabolic health spectrum, demonstrating reproducible diagnostic performance and specifying both known and novel metabolic pathways relevant to MASLD (central carbon and amino acid metabolism, hepatocyte regeneration, inflammation, fibrosis, insulin sensitivity). A parsimonious proteomic signature of MASLD was associated with a protection from MASLD and its related multi-system metabolic consequences in >26000 free-living individuals, with an additive effect to polygenic risk. The MASLD proteome was encoded by genes that demonstrated transcriptional enrichment in liver, with spatial transcriptional activity in areas of steatosis in human liver biopsy and dynamicity for select targets in human liver across stages of steatosis. We replicated several top relations from proteomics and spatial tissue transcriptomics in a humanized "liver-on-a-chip" model of MASLD, highlighting the power of a full translational approach to discovery in MASLD. Collectively, these results underscore utility of blood-based proteomics as a dynamic "liquid biopsy" of human liver relevant to clinical biomarker and mechanistic applications.

Proteomic analysis of cardiorespiratory fitness for prediction of mortality and multisystem disease risks.

Despite the wide effects of cardiorespiratory fitness (CRF) on metabolic, cardiovascular, pulmonary and neurological health, challenges in the feasibility and reproducibility of CRF measurements have impeded its use for clinical decision-making. Here we link proteomic profiles to CRF in 14,145 individuals across four international cohorts with diverse CRF ascertainment methods to establish, validate and characterize a proteomic CRF score. In a cohort of around 22,000 individuals in the UK Biobank, a proteomic CRF score was associated with a reduced risk of all-cause mortality (unadjusted hazard ratio 0.50 (95% confidence interval 0.48-0.52) per 1 s.d. increase). The proteomic CRF score was also associated with multisystem disease risk and provided risk reclassification and discrimination beyond clinical risk factors, as well as modulating high polygenic risk of certain diseases. Finally, we observed dynamicity of the proteomic CRF score in individuals who undertook a 20-week exercise training program and an association of the score with the degree of the effect of training on CRF, suggesting potential use of the score for personalization of exercise recommendations. These results indicate that population-based proteomics provides biologically relevant molecular readouts of CRF that are additive to genetic risk, potentially modifiable and clinically translatable.