Response eQTLs, chromatin accessibility, and 3D chromatin structure in chondrocytes provide mechanistic insight into osteoarthritis risk.

Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWAS) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. Integrating expression quantitative trait loci (eQTL), 3D chromatin structure, and other genomic approaches with OA GWAS data offers a promising approach to elucidate disease mechanisms; however, comprehensive eQTL maps in OA-relevant tissues and conditions remain scarce. We mapped gene expression, chromatin accessibility, and 3D chromatin structure in primary human articular chondrocytes in both resting and OA-mimicking conditions. We identified thousands of differentially expressed genes, including those associated with differences in sex and age. RNA-seq in chondrocytes from 101 donors across two conditions uncovered 3782 unique eGenes, including 420 that exhibited strong and significant condition-specific effects. Colocalization with OA GWAS signals revealed 13 putative OA risk genes, 10 of which have not been previously identified. Chromatin accessibility and 3D chromatin structure provided insights into the mechanisms and conditional specificity of these variants. Our findings shed light on OA pathogenesis and highlight potential targets for therapeutic development. Highlights: ∘ Comprehensive analysis of sex- and age-related global gene expression in human chondrocytes revealed differences that correlate with osteoarthritis ∘ First response eQTLs in chondrocytes treated with an OA-related stimulus ∘ Deeply sequenced Hi-C in resting and activated chondrocytes helps connect OA risk variants to their putative causal genes ∘ Colocalization analysis reveals 13 (including 10 novel) putative OA risk genes.

The tidyomics ecosystem: Enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor1 provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming2 offers a revolutionary standard for data organisation and manipulation. Here, we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning, and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analysing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas3, spanning six data frameworks and ten analysis tools.

The tidyomics ecosystem: enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis and integration. Addressing these challenges, Bioconductor provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming offers a revolutionary data organization and manipulation standard. Here we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analyzing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas, spanning six data frameworks and ten analysis tools.

Exploring the associations between skeletal muscle echogenicity and physical function in aging adults: A systematic review with meta-analyses.

BACKGROUND: Assessment and quantification of skeletal muscle within the aging population is vital for diagnosis, treatment, and injury/disease prevention. The clinical availability of assessing muscle quality through diagnostic ultrasound presents an opportunity to be utilized as a screening tool for function-limiting diseases. However, relationships between muscle echogenicity and clinical functional assessments require authoritative analysis. Thus, we aimed to (a) synthesize the literature to assess the relationships between skeletal muscle echogenicity and physical function in older adults (≥60 years), (b) perform pooled analyses of relationships between skeletal muscle echogenicity and physical function, and (c) perform sub-analyses to determine between-muscle relationships. METHODS: CINAHL, Embase, MEDLINE, PubMed, and Web of Science databases were systematically searched to identify articles relating skeletal muscle echogenicity to physical function in older adults. Risk-of-bias assessments were conducted along with funnel plot examination. Meta-analyses with and without sub-analyses for individual muscles were performed utilizing Fisher's Z transformation for the most common measures of physical function. Fisher's Z was back-transformed to Pearson's r for interpretation. RESULTS: Fifty-one articles (n = 5095, female = ∼2759, male = ∼2301, 72.5 ± 5.8 years, mean ± SD (1 study did not provide sex descriptors)) were extracted for review, with previously unpublished data obtained from the authors of 13 studies. The rectus femoris (n = 34) and isometric knee extension strength (n = 22) were the most accessed muscle and physical qualities, respectively. The relationship between quadriceps echogenicity and knee extensor strength was moderate (n = 2924, r = -0.36 (95% confidence interval: -0.38 to -0.32), p < 0.001), with all other meta-analyses (grip strength, walking speed, sit-to-stand, timed up-and-go) resulting in slightly weaker correlations (r:  -0.34 to -0.23, all p < 0.001). Sub-analyses determined minimal differences in predictive ability between muscle groups, although combining muscles (e.g., rectus femoris + vastus lateralis) often resulted in stronger correlations with maximal strength. CONCLUSION: While correlations were modest, the affordable, portable, and noninvasive ultrasonic assessment of muscle quality was a consistent predictor of physical function in older adults. Minimal between-muscle differences suggest that echogenicity estimates of muscle quality are systemic. Therefore, practitioners may be able to scan a single muscle to estimate full-body skeletal muscle quality/composition, while researchers should consider combining multiple muscles to strengthen the model.

Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain.

Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.

Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification.

CRISPR base editing screens enable analysis of disease-associated variants at scale; however, variable efficiency and precision confounds the assessment of variant-induced phenotypes. Here, we provide an integrated experimental and computational pipeline that improves estimation of variant effects in base editing screens. We use a reporter construct to measure guide RNA (gRNA) editing outcomes alongside their phenotypic consequences and introduce base editor screen analysis with activity normalization (BEAN), a Bayesian network that uses per-guide editing outcomes provided by the reporter and target site chromatin accessibility to estimate variant impacts. BEAN outperforms existing tools in variant effect quantification. We use BEAN to pinpoint common regulatory variants that alter low-density lipoprotein (LDL) uptake, implicating previously unreported genes. Additionally, through saturation base editing of LDLR, we accurately quantify missense variant pathogenicity that is consistent with measurements in UK Biobank patients and identify underlying structural mechanisms. This work provides a widely applicable approach to improve the power of base editing screens for disease-associated variant characterization.

Machine learning methods for predicting guide RNA effects in CRISPR epigenome editing experiments.

CRISPR epigenomic editing technologies enable functional interrogation of non-coding elements. However, current computational methods for guide RNA (gRNA) design do not effectively predict the power potential, molecular and cellular impact to optimize for efficient gRNAs, which are crucial for successful applications of these technologies. We present "launch-dCas9" (machine LeArning based UNified CompreHensive framework for CRISPR-dCas9) to predict gRNA impact from multiple perspectives, including cell fitness, wildtype abundance (gauging power potential), and gene expression in single cells. Our launchdCas9, built and evaluated using experiments involving >1 million gRNAs targeted across the human genome, demonstrates relatively high prediction accuracy (AUC up to 0.81) and generalizes across cell lines. Method-prioritized top gRNA(s) are 4.6-fold more likely to exert effects, compared to other gRNAs in the same cis-regulatory region. Furthermore, launchdCas9 identifies the most critical sequence-related features and functional annotations from >40 features considered. Our results establish launch-dCas9 as a promising approach to design gRNAs for CRISPR epigenomic experiments.

Blood Flow Restriction and Veterans With Multiple Sclerosis and Advanced Disability: Protocol for a Randomized Controlled Trial.

OBJECTIVE: The purpose of this study will be to determine the efficacy of low intensity lower extremity resistance training with and without blood flow restriction (BFR) on quadriceps muscle strength and thickness in veterans with advanced multiple sclerosis (MS). METHODS: This will be an assessor-blinded, 2-group (1 to 1 allocation) randomized controlled trial targeting an enrollment of 58 participants with advanced MS as defined by Patient-Determined Disease Steps scale levels 4 to 7. Both groups will complete 10 weeks of twice weekly low-load resistance training (20%-30% of 1-repetition max) targeting knee and hip extension, knee flexion, and ankle plantarflexion. The intervention group will perform all training using BFR, with limb occlusion pressures between 60% and 80% of maximal limb occlusion pressure. Primary outcomes will be quadriceps muscle strength and thickness. Secondary outcomes will include knee flexion and ankle plantarflexion strength, functional mobility, physical activity, and patient-reported measures. All outcomes will be assessed at baseline before the intervention, immediately after the intervention, and at a 2-month follow-up assessment. The change between groups postintervention and after the 2-month follow-up will be reported for all outcomes. All analyses will assume a 2-sided test of hypothesis (α = .05). IMPACT: There is very little evidence for the efficacy of exercise interventions in people with MS who have advanced mobility disability. Resistance training with BFR may be an important approach for people with advanced MS who may not tolerate more conventional, moderate-to-high intensity resistance training. The results of this study will inform clinicians regarding exercise decisions for people with advanced MS and future investigations on the role of BFR in people with MS.

Diffsig: Associating Risk Factors with Mutational Signatures.

BACKGROUND: Somatic mutational signatures elucidate molecular vulnerabilities to therapy, and therefore detecting signatures and classifying tumors with respect to signatures has clinical value. However, identifying the etiology of the mutational signatures remains a statistical challenge, with both small sample sizes and high variability in classification algorithms posing barriers. As a result, few signatures have been strongly linked to particular risk factors. METHODS: Here, we develop a statistical model, Diffsig, for estimating the association of one or more continuous or categorical risk factors with DNA mutational signatures. Diffsig takes into account the uncertainty associated with assigning signatures to samples as well as multiple risk factors' simultaneous effect on observed DNA mutations. RESULTS: We applied Diffsig to breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development. In simulation, our model was capable of accurately estimating expected associations in a variety of contexts. CONCLUSIONS: Diffsig allows researchers to quantify and perform inference on the associations of risk factors with mutational signatures. IMPACT: We expect Diffsig to provide more robust associations of risk factors with signatures to lead to better understanding of the tumor development process and improved models of tumorigenesis.

Exercise for patients with chronic kidney disease: from cells to systems to function.

Chronic kidney disease (CKD) is among the leading causes of death and disability, affecting an estimated 800 million adults globally. The underlying pathophysiology of CKD is complex creating challenges to its management. Primary risk factors for the development and progression of CKD include diabetes mellitus, hypertension, age, obesity, diet, inflammation, and physical inactivity. The high prevalence of diabetes and hypertension in patients with CKD increases the risk for secondary consequences such as cardiovascular disease and peripheral neuropathy. Moreover, the increased prevalence of obesity and chronic levels of systemic inflammation in CKD have downstream effects on critical cellular functions regulating homeostasis. The combination of these factors results in the deterioration of health and functional capacity in those living with CKD. Exercise offers protective benefits for the maintenance of health and function with age, even in the presence of CKD. Despite accumulating data supporting the implementation of exercise for the promotion of health and function in patients with CKD, a thorough description of the responses and adaptations to exercise at the cellular, system, and whole body levels is currently lacking. Therefore, the purpose of this review is to provide an up-to-date comprehensive review of the effects of exercise training on vascular endothelial progenitor cells at the cellular level; cardiovascular, musculoskeletal, and neural factors at the system level; and physical function, frailty, and fatigability at the whole body level in patients with CKD.

Robotic transversus abdominis release: A paradigm shift in complex abdominal wall surgery?

Abdominal wall reconstruction techniques have evolved significantly over the last fifty years and continue to do so at an increasing pace. Beginning with open incisional hernia repair with bilateral rectus myofascial release, multiple techniques to offset tension at the midline by exploring options of layered myofascial release have been described. This article reviews the history, technique, advancements, and future of myofascial release in abdominal wall reconstruction leading from the open Rives-Stoppa repair to the robotic-assisted iteration of the transversus abdominis release.

Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits.

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with ≥2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants.

Genome-wide association studies (GWASs) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium makes it challenging to discern causal variants. We performed a massively parallel reporter assay (MPRA) on 5,173 fine-mapped schizophrenia GWAS variants in primary human neural progenitors and identified 439 variants with allelic regulatory effects (MPRA-positive variants). Transcription factor binding had modest predictive power, while fine-map posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit expressive quantitative trait loci signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. To predict the combinatorial effect of MPRA-positive variants on gene regulation, we propose an accessibility-by-contact model that combines MPRA-measured allelic activity with neuronal chromatin architecture.

Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features.

Three-dimensional (3D) chromatin structure has been shown to play a role in regulating gene transcription during biological transitions. Although our understanding of loop formation and maintenance is rapidly improving, much less is known about the mechanisms driving changes in looping and the impact of differential looping on gene transcription. One limitation has been a lack of well-powered differential looping data sets. To address this, we conducted a deeply sequenced Hi-C time course of megakaryocyte development comprising four biological replicates and 6 billion reads per time point. Statistical analysis revealed 1503 differential loops. Gained loop anchors were enriched for AP-1 occupancy and were characterized by large increases in histone H3K27ac (over 11-fold) but relatively small increases in CTCF and RAD21 binding (1.26- and 1.23-fold, respectively). Linear modeling revealed that changes in histone H3K27ac, chromatin accessibility, and JUN binding were better correlated with changes in looping than RAD21 and almost as well correlated as CTCF. Changes to epigenetic features between-rather than at-boundaries were highly predictive of changes in looping. Together these data suggest that although CTCF and RAD21 may be the core machinery dictating where loops form, other features (both at the anchors and within the loop boundaries) may play a larger role than previously anticipated in determining the relative loop strength across cell types and conditions.

Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification.

CRISPR base editing screens are powerful tools for studying disease-associated variants at scale. However, the efficiency and precision of base editing perturbations vary, confounding the assessment of variant-induced phenotypic effects. Here, we provide an integrated pipeline that improves the estimation of variant impact in base editing screens. We perform high-throughput ABE8e-SpRY base editing screens with an integrated reporter construct to measure the editing efficiency and outcomes of each gRNA alongside their phenotypic consequences. We introduce BEAN, a Bayesian network that accounts for per-guide editing outcomes and target site chromatin accessibility to estimate variant impacts. We show this pipeline attains superior performance compared to existing tools in variant classification and effect size quantification. We use BEAN to pinpoint common variants that alter LDL uptake, implicating novel genes. Additionally, through saturation base editing of LDLR, we enable accurate quantitative prediction of the effects of missense variants on LDL-C levels, which aligns with measurements in UK Biobank individuals, and identify structural mechanisms underlying variant pathogenicity. This work provides a widely applicable approach to improve the power of base editor screens for disease-associated variant characterization.

Comprehensive evaluation of methods for differential expression analysis of metatranscriptomics data.

Understanding the function of the human microbiome is important but the development of statistical methods specifically for the microbial gene expression (i.e. metatranscriptomics) is in its infancy. Many currently employed differential expression analysis methods have been designed for different data types and have not been evaluated in metatranscriptomics settings. To address this gap, we undertook a comprehensive evaluation and benchmarking of 10 differential analysis methods for metatranscriptomics data. We used a combination of real and simulated data to evaluate performance (i.e. type I error, false discovery rate and sensitivity) of the following methods: log-normal (LN), logistic-beta (LB), MAST, DESeq2, metagenomeSeq, ANCOM-BC, LEfSe, ALDEx2, Kruskal-Wallis and two-part Kruskal-Wallis. The simulation was informed by supragingival biofilm microbiome data from 300 preschool-age children enrolled in a study of childhood dental disease (early childhood caries, ECC), whereas validations were sought in two additional datasets from the ECC study and an inflammatory bowel disease study. The LB test showed the highest sensitivity in both small and large samples and reasonably controlled type I error. Contrarily, MAST was hampered by inflated type I error. Upon application of the LN and LB tests in the ECC study, we found that genes C8PHV7 and C8PEV7, harbored by the lactate-producing Campylobacter gracilis, had the strongest association with childhood dental disease. This comprehensive model evaluation offers practical guidance for selection of appropriate methods for rigorous analyses of differential expression in metatranscriptomics. Selection of an optimal method increases the possibility of detecting true signals while minimizing the chance of claiming false ones.

Use of the Carlino Technique in Chronic Total Occlusion Percutaneous Coronary Intervention.

We examined the outcomes of the Carlino technique in chronic total occlusion (CTO) percutaneous coronary interventions (PCIs). We analyzed the baseline clinical and angiographic characteristics and outcomes of 128 CTO PCIs that included the Carlino technique at 22 US and no-US centers between 2016 and 2023. The Carlino technique was used in 128 (2.8%) of 4,508 cases that used anterograde dissection and reentry (78.9%) or the retrograde approach (21.1%) during the study period, and it increased steadily over time (from 0.0% in 2016 to 8.3% in 2023). The mean patient age was 65.6 ± 9.7 years, and 88.7% of the patients were men with high prevalence of hypertension (89.1%) and dyslipidemia (80.2%). The Carlino technique was more commonly used in cases with moderate to severe calcification (77.2% vs 55.5%, p <0.001) with higher J-CTO (3.3 ± 0.9 vs 3.0 ± 1.1, p = 0.007), Prospective Global Registry for the Study of Chronic Total Occlusion Intervention (PROGRESS-CTO) (1.7 ± 1.0 vs 1.4 ± 1.0, p = 0.001), PROGRESS-CTO Mortality (2.6 ± 0.9 vs 2.0 ± 0.9, p = 0.013) and PROGRESS-CTO Perforation (3.7 ± 1.1 vs 3.5 ± 1.0, p = 0.029) scores. Carlino cases had longer procedure and fluoroscopy time, and higher contrast volume and radiation dose. Carlino cases had lower technical (65.6% vs 78.5%, p <0.001) and procedural (63.3% vs 76.3%, p <0.001) success, similar major adverse cardiac events (6.2% vs 3.2%, p = 0.101) and higher incidence of pericardiocentesis (3.9% vs 1.3%, p = 0.042), perforation (18.0% vs 8.9%, p = 0.001) and contrast-induced acute kidney injury (2.3% vs 0.4%, p = 0.012). The Carlino technique was associated with higher procedural success when used for retrograde crossing (81.5% vs 58.4%, p = 0.047). The Carlino technique is increasingly being used in CTO PCI especially for higher complexity lesions.

Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis.

The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk post-mortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA-editing and alternative polyadenylation (APA), within a cell-type-specific population of human neural progenitors and neurons. More RNA-editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting genetically mediated post-transcriptional regulation during brain development lead to differences in brain function.

Impact of calcium on the procedural techniques and outcomes of chronic total occlusion percutaneous coronary intervention.

BACKGROUND: Coronary calcification is common and increases the difficulty of chronic total occlusion (CTO) percutaneous coronary intervention (PCI). METHODS: We examined the impact of calcium on procedural outcomes of 13,079 CTO PCIs performed in 12,799 patients at 46 US and non-US centers between 2012 and 2023. RESULTS: Moderate or severe calcification was present in 46.6% of CTO lesions. Patients whose lesions were calcified were older and more likely to have had prior coronary artery bypass graft surgery. Calcified lesions were more complex with higher J-CTO score (3.0 ± 1.1 vs. 1.9 ± 1.2; p < 0.001) and lower technical (83.0% vs. 89.9%; p < 0.001) and procedural (81.0% vs. 89.1%; p < 0.001) success rates compared with mildly calcified or non-calcified CTO lesions. The retrograde approach was more commonly used among cases with moderate/severe calcification (40.3% vs. 23.5%; p < 0.001). Balloon angioplasty (76.6%) was the most common lesion preparation technique for calcified lesions, followed by rotational atherectomy (7.3%), laser atherectomy (3.4%) and, intravascular lithotripsy (3.4%). The incidence of major adverse cardiovascular events (MACE) was higher in cases with moderate or severe calcification (3.0% vs. 1.2%; p < 0.001), as was the incidence of perforation (6.5% vs. 3.4%; p < 0.001). On multivariable analysis, the presence of moderate/severe calcification was independently associated with lower technical success (odds ratio, OR = 0.73, 95% CI: 0.63-0.84) and higher MACE (OR = 2.33, 95% CI: 1.66-3.27). CONCLUSIONS: Moderate/severe calcification was present in nearly half of CTO lesions, and was associated with higher utilization of the retrograde approach, lower technical and procedural success rates, and higher incidence of in-hospital MACE.

Cell-Type Composition Affects Adipose Gene Expression Associations With Cardiometabolic Traits.

Understanding differences in adipose gene expression between individuals with different levels of clinical traits may reveal the genes and mechanisms leading to cardiometabolic diseases. However, adipose is a heterogeneous tissue. To account for cell-type heterogeneity, we estimated cell-type proportions in 859 subcutaneous adipose tissue samples with bulk RNA sequencing (RNA-seq) using a reference single-nuclear RNA-seq data set. Cell-type proportions were associated with cardiometabolic traits; for example, higher macrophage and adipocyte proportions were associated with higher and lower BMI, respectively. We evaluated cell-type proportions and BMI as covariates in tests of association between >25,000 gene expression levels and 22 cardiometabolic traits. For >95% of genes, the optimal, or best-fit, models included BMI as a covariate, and for 79% of associations, the optimal models also included cell type. After adjusting for the optimal covariates, we identified 2,664 significant associations (P ≤ 2e-6) for 1,252 genes and 14 traits. Among genes proposed to affect cardiometabolic traits based on colocalized genome-wide association study and adipose expression quantitative trait locus signals, 25 showed a corresponding association between trait and gene expression levels. Overall, these results suggest the importance of modeling cell-type proportion when identifying gene expression associations with cardiometabolic traits.