Design and Pilot Results from Million Veteran Program Return Of Actionable Genetic Results (MVP-ROAR) Study.

BACKGROUND: As a mega-biobank linked to a national healthcare system, the Million Veteran Program (MVP) can directly improve the health care of participants. To determine the feasibility and outcomes of returning medically actionable genetic results to MVP participants, the program launched the MVP Return Of Actionable Results (MVP-ROAR) Study, with familial hypercholesterolemia (FH) as an exemplar actionable condition. METHODS: The MVP-ROAR Study consists of a completed single-arm pilot phase and an ongoing randomized clinical trial (RCT), in which MVP participants are recontacted and invited to receive clinical confirmatory gene sequencing testing and a telegenetic counseling intervention. The primary outcome of the RCT is 6-month change in low-density lipoprotein cholesterol (LDL-C) between participants receiving results at baseline and those receiving results after 6 months. RESULTS: The pilot developed processes to identify and recontact participants nationally with probable pathogenic variants in low-density lipoprotein receptor (LDLR) on the MVP genotype array, invite them to clinical confirmatory gene sequencing, and deliver a telegenetic counseling intervention. Among participants in the pilot phase, 8 (100%) had active statin prescriptions after 6 months. Results were shared with 16 first-degree family members. Six-month ΔLDL-C (low-density lipoprotein cholesterol) after the genetic counseling intervention was -37 mg/dL (95% CI: -12 to -61; p=0.03). The ongoing RCT will determine between-arm differences in this primary outcome. CONCLUSION: While underscoring the importance of clinical confirmation of research results, the pilot phase of the MVP-ROAR Study marks a turning point in MVP and demonstrates the feasibility of returning genetic results to participants and their providers. The ongoing RCT will contribute to understanding how such a program might improve patient health care and outcomes.

Chemerin in Participants with or without Insulin Resistance and Diabetes.

Chemerin is a chemokine/adipokine, regulating inflammation, adipogenesis and energy metabolism whose activity depends on successive proteolytic cleavages at its C-terminus. Chemerin levels and processing are correlated with insulin resistance. We hypothesized that chemerin processing would be higher in individuals with type 2 diabetes (T2D) and in those who are insulin resistant (IR). This hypothesis was tested by characterizing different chemerin forms by specific ELISA in the plasma of 18 participants with T2D and 116 without T2D who also had their insulin resistance measured by steady-state plasma glucose (SSPG) concentration during an insulin suppression test. This approach enabled us to analyze the association of chemerin levels with a direct measure of insulin resistance (SSPG concentration). Participants were divided into groups based on their degree of insulin resistance using SSPG concentration tertiles: insulin sensitive (IS, SSPG ≤ 91 mg/dL), intermediate IR (IM, SSPG 92-199 mg/dL), and IR (SSPG ≥ 200 mg/dL). Levels of different chemerin forms were highest in patients with T2D, second highest in individuals without T2D who were IR, and lowest in persons without T2D who were IM or IS. In the whole group, chemerin levels positively correlated with both degree of insulin resistance (SSPG concentration) and adiposity (BMI). Participants with T2D and those without T2D who were IR had the most proteolytic processing of chemerin, resulting in higher levels of both cleaved and degraded chemerin. This suggests that increased inflammation in individuals who have T2D or are IR causes more chemerin processing.

Is it time for a paradigm shift? Inclusion of APOE on genetic dyslipidemia panels.

APOE codes for apolipoprotein E (ApoE), which plays an important role in lipid and lipoprotein metabolism and homeostasis of tissue lipid content. Several variants in APOE have been associated with inherited dyslipidemias, and a subsequent increased risk of developing premature coronary artery disease (CAD). However, these variants and their impact on risk can be thought of on a spectrum, with some being more monogenic in nature, and others contributing in a polygenic/multifactorial manner. Despite these known associations, there is often hesitancy around ordering APOE genetic testing due to the association with Alzheimer's disease. This paper aims to catalyze discussion around APOE testing and counseling strategies, highlight the nuances around this topic, and advocate for inclusion of APOE testing on dyslipidemia panels when an inherited dyslipidemia is suspected.

Lac-Phe mediates the effects of metformin on food intake and body weight.

Metformin is a widely prescribed anti-diabetic medicine that also reduces body weight. There is ongoing debate about the mechanisms that mediate metformin's effects on energy balance. Here, we show that metformin is a powerful pharmacological inducer of the anorexigenic metabolite N-lactoyl-phenylalanine (Lac-Phe) in cells, in mice and two independent human cohorts. Metformin drives Lac-Phe biosynthesis through the inhibition of complex I, increased glycolytic flux and intracellular lactate mass action. Intestinal epithelial CNDP2+ cells, not macrophages, are the principal in vivo source of basal and metformin-inducible Lac-Phe. Genetic ablation of Lac-Phe biosynthesis in male mice renders animals resistant to the effects of metformin on food intake and body weight. Lastly, mediation analyses support a role for Lac-Phe as a downstream effector of metformin's effects on body mass index in participants of a large population-based observational cohort, the Multi-Ethnic Study of Atherosclerosis. Together, these data establish Lac-Phe as a critical mediator of the body weight-lowering effects of metformin.

Development and utility of a clinical research informatics application for participant recruitment and workflow management for a return of results pilot trial in familial hypercholesterolemia in the Million Veteran Program.

Objective: The development of clinical research informatics tools and workflow processes associated with re-engaging biobank participants has become necessary as genomic repositories increasingly consider the return of actionable research results. Materials and Methods: Here we describe the development and utility of an informatics application for participant recruitment and enrollment management for the Veterans Affairs Million Veteran Program Return Of Actionable Results Study, a randomized controlled pilot trial returning individual genetic results associated with familial hypercholesterolemia. Results: The application is developed in Python-Flask and was placed into production in November 2021. The application includes modules for chart review, medication reconciliation, participant contact and biospecimen logging, survey recording, randomization, and documentation of genetic counseling and result disclosure. Three primary users, a genetic counselor and two research coordinators, and 326 Veteran participants have been integrated into the system as of February 23, 2023. The application has successfully handled 3367 task requests involving greater than 95 000 structured data points. Specifically, application users have recorded 326 chart reviews, 867 recruitment telephone calls, 158 telephone-based surveys, and 61 return of results genetic counseling sessions, among other available study tasks. Conclusion: The development of usable, customizable, and secure informatics tools will become increasingly important as large genomic repositories begin to return research results at scale. Our work provides a proof-of-concept for developing and using such tools to aid in managing the return of results process within a national biobank.

Generation of two induced pluripotent stem cell lines from healthy patients of African American ancestry.

Stem cells are a resourceful tool for investigating cardiovascular disease in the context of race and gender. Once derived from blood or skin cells, the reprogrammed induced pluripotent stem cells (iPSCs) adopt an embryonic-like pluripotent state, enabling researchers to develop drug screening or disease modeling platforms. Here, we generated two iPSC lines from peripheral blood mononuclear cells (PBMCs) of two healthy African American patients. Both lines display the usual morphology of pluripotent stem cells, demonstrate elevated expression of pluripotent markers, show normal karyotype, and differentiate into all three germ layers in vitro.

A functional genomic framework to elucidate novel causal non-alcoholic fatty liver disease genes.

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver pathology in western countries, with serious public health consequences. Efforts to identify causal genes for NAFLD have been hampered by the relative paucity of human data from gold-standard magnetic resonance quantification of hepatic fat. To overcome insufficient sample size, genome-wide association studies using NAFLD surrogate phenotypes have been used, but only a small number of loci have been identified to date. In this study, we combined GWAS of NAFLD composite surrogate phenotypes with genetic colocalization studies followed by functional in vitro screens to identify bona fide causal genes for NAFLD. Approach & Results: We used the UK Biobank to explore the associations of our novel NAFLD score, and genetic colocalization to prioritize putative causal genes for in vitro validation. We created a functional genomic framework to study NAFLD genes in vitro using CRISPRi. Our data identify VKORC1, TNKS, LYPLAL1 and GPAM as regulators of lipid accumulation in hepatocytes and suggest the involvement of VKORC1 in the lipid storage related to the development of NAFLD. Conclusions: Complementary genetic and genomic approaches are useful for the identification of NAFLD genes. Our data supports VKORC1 as a bona fide NAFLD gene. We have established a functional genomic framework to study at scale putative novel NAFLD genes from human genetic association studies.

Trends of Lipid Concentrations, Awareness, Evaluation, and Treatment in Severe Dyslipidemia in US Adults.

OBJECTIVE: To evaluate the contemporary trends of lipid concentrations, cholesterol evaluation, hypercholesterolemia awareness, and statin use among individuals with severe dyslipidemia (low-density lipoprotein cholesterol [LDL-C] level ≥190 mg/dL) between 2011 and 2020. PATIENTS AND METHODS: This serial cross-sectional analysis included nonpregnant adults ≥20 years of age from the National Health and Nutrition Examination Survey between 2011 and 2020. Age-adjusted weighted trends of LDL-C, triglycerides, cholesterol evaluation in the past 5 years, hypercholesterolemia awareness, and documented statin use among individuals with severe dyslipidemia were estimated. RESULTS: Among 24,722 participants included, the prevalence of severe dyslipidemia was 5.4% (SE: 0.2%) which was stable across the study period (Ptrend=.78). Among individuals with severe dyslipidemia (mean age: 55.3 [SE: 0.7] years; 52.2% females; 68.8% non-Hispanic White), LDL-C (224.3 [SE: 4.2] mg/dL in 2011-2012 to 224.2 [SE: 4.6] mg/dL in 2017-2020; Ptrend =.83), and triglyceride (123.3 [SE: 1.1] mg/dL in 2011-2012 to 101.8 [SE: 1.1] mg/dL in 2017-2020; Ptrend=.13), levels remained stable from 2011 to 2020. The rates of cholesterol evaluation in the past 5 years (72.0% [SE: 5.7%] in 2011-2012 to 78.0% [SE: 4.8%] in 2017-2020; Ptrend=.91), hypercholesterolemia awareness (48.1% [SE: 5.5%] in 2011-2012 to 51.9% [SE: 5.8%] in 2017- 2020; Ptrend=.77), and documented statin use (34.7% [SE: 4.5%] in 2011-2012 to 33.4% [SE: 4.0%] in 2017-2020; Ptrend=.28) remained stagnant in individuals with severe dyslipidemia between 2011 and 2020. CONCLUSION: Among individuals with severe dyslipidemia, cholesterol evaluation and hypercholesterolemia awareness rates were stable at ∼75% and ∼50% in the past decade. Only ∼34% of individuals with severe dyslipidemia took statins between 2011 and 2020, which likely contributed to the stable LDL-C levels noted across the study period. Further investigations into the determinants of statin use and adherence to statins are needed.

Lac-Phe mediates the anti-obesity effect of metformin.

Metformin is a widely prescribed anti-diabetic medicine that also reduces body weight. The mechanisms that mediate metformin's effects on energy balance remain incompletely defined. Here we show that metformin is a powerful pharmacological inducer of the anorexigenic metabolite Lac-Phe in mice as well as in two independent human cohorts. In cell culture, metformin drives Lac-Phe biosynthesis via inhibition of complex I, increased glycolytic flux, and intracellular lactate mass action. Other biguanides and structurally distinct inhibitors of oxidative phosphorylation also increase Lac-Phe levels in vitro. Genetic ablation of CNDP2, the principal biosynthetic enzyme for Lac-Phe, in mice renders animals resistant to metformin's anorexigenic and anti-obesity effects. Mediation analyses also support a role for Lac-Phe in metformin's effect on body mass index in humans. These data establish the CNDP2/Lac-Phe pathway as a critical mediator of the effects of metformin on energy balance.

RNA interference targeting ANGPTL3 for triglyceride and cholesterol lowering: phase 1 basket trial cohorts.

Elevated triglycerides and non-high-density lipoprotein cholesterol (HDL-C) are risk factors for atherosclerotic cardiovascular disease (ASCVD). ARO-ANG3 is an RNA interference therapy that targets angiopoietin-like protein 3 (ANGPTL3), a regulator of lipoprotein metabolism. This first-in-human, phase 1, randomized, placebo-controlled, open-label trial investigated single and repeat ARO-ANG3 doses in four cohorts of fifty-two healthy participants and one cohort of nine participants with hepatic steatosis, part of a basket trial. Safety (primary objective) and pharmacokinetics (in healthy participants) and pharmacodynamics (secondary objectives) of ARO-ANG3 were evaluated. ARO-ANG3 was generally well tolerated, with similar frequencies of treatment-emergent adverse events in active and placebo groups. Systemic absorption of ARO-ANG3 in healthy participants was rapid and sustained, with a mean Tmax of 6.0-10.5 h and clearance from plasma within 24-48 h after dosing with a mean t½ of 3.9-6.6 h. In healthy participants, ARO-ANG3 treatment reduced ANGPTL3 (mean -45% to -78%) 85 days after dose. Reductions in triglyceride (median -34% to -54%) and non-HDL-C (mean -18% to -29%) (exploratory endpoints) concentrations occurred with the three highest doses. These early-phase data support ANGPTL3 as a potential therapeutic target for ASCVD treatment. ClinicalTrials.gov identifier: NCT03747224.

Principles for Health Information Collection, Sharing, and Use: A Policy Statement From the American Heart Association.

The evolution of the electronic health record, combined with advances in data curation and analytic technologies, increasingly enables data sharing and harmonization. Advances in the analysis of health-related and health-proxy information have already accelerated research discoveries and improved patient care. This American Heart Association policy statement discusses how broad data sharing can be an enabling driver of progress by providing data to develop, test, and benchmark innovative methods, scalable insights, and potential new paradigms for data storage and workflow. Along with these advances come concerns about the sensitive nature of some health data, equity considerations about the involvement of historically excluded communities, and the complex intersection of laws attempting to govern behavior. Data-sharing principles are therefore necessary across a wide swath of entities, including parties who collect health information, funders, researchers, patients, legislatures, commercial companies, and regulatory departments and agencies. This policy statement outlines some of the key equity and legal background relevant to health data sharing and responsible management. It then articulates principles that will guide the American Heart Association's engagement in public policy related to data collection, sharing, and use to continue to inform its work across the research enterprise, as well as specific examples of how these principles might be applied in the policy landscape. The goal of these principles is to improve policy to support the use or reuse of health information in ways that are respectful of patients and research participants, equitable in impact in terms of both risks and potential benefits, and beneficial across broad and demographically diverse communities in the United States.

A single-cell CRISPRi platform for characterizing candidate genes relevant to metabolic disorders in human adipocytes.

CROP-Seq combines gene silencing using CRISPR interference with single-cell RNA sequencing. Here, we applied CROP-Seq to study adipogenesis and adipocyte biology. Human preadipocyte SGBS cell line expressing KRAB-dCas9 was transduced with a sgRNA library. Following selection, individual cells were captured using microfluidics at different timepoints during adipogenesis. Bioinformatic analysis of transcriptomic data was used to determine the knockdown effects, the dysregulated pathways, and to predict cellular phenotypes. Single-cell transcriptomes recapitulated adipogenesis states. For all targets, over 400 differentially expressed genes were identified at least at one timepoint. As a validation of our approach, the knockdown of PPARG and CEBPB (which encode key proadipogenic transcription factors) resulted in the inhibition of adipogenesis. Gene set enrichment analysis generated hypotheses regarding the molecular function of novel genes. MAFF knockdown led to downregulation of transcriptional response to proinflammatory cytokine TNF-α in preadipocytes and to decreased CXCL-16 and IL-6 secretion. TIPARP knockdown resulted in increased expression of adipogenesis markers. In summary, this powerful, hypothesis-free tool can identify novel regulators of adipogenesis, preadipocyte, and adipocyte function associated with metabolic disease.NEW & NOTEWORTHY Genomics efforts led to the identification of many genomic loci that are associated with metabolic traits, many of which are tied to adipose tissue function. However, determination of the causal genes, and their mechanism of action in metabolism, is a time-consuming process. Here, we use an approach to determine the transcriptional outcome of candidate gene knockdown for multiple genes at the same time in a human cell model of adipogenesis.

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models.

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on these widely used in vitro models of human and mouse adipogenesis, and on cell-to-cell variability during this process.

Plasma proteomic signatures of a direct measure of insulin sensitivity in two population cohorts.

AIMS/HYPOTHESIS: The euglycaemic-hyperinsulinaemic clamp (EIC) is the reference standard for the measurement of whole-body insulin sensitivity but is laborious and expensive to perform. We aimed to assess the incremental value of high-throughput plasma proteomic profiling in developing signatures correlating with the M value derived from the EIC. METHODS: We measured 828 proteins in the fasting plasma of 966 participants from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study and 745 participants from the Uppsala Longitudinal Study of Adult Men (ULSAM) using a high-throughput proximity extension assay. We used the least absolute shrinkage and selection operator (LASSO) approach using clinical variables and protein measures as features. Models were tested within and across cohorts. Our primary model performance metric was the proportion of the M value variance explained (R2). RESULTS: A standard LASSO model incorporating 53 proteins in addition to routinely available clinical variables increased the M value R2 from 0.237 (95% CI 0.178, 0.303) to 0.456 (0.372, 0.536) in RISC. A similar pattern was observed in ULSAM, in which the M value R2 increased from 0.443 (0.360, 0.530) to 0.632 (0.569, 0.698) with the addition of 61 proteins. Models trained in one cohort and tested in the other also demonstrated significant improvements in R2 despite differences in baseline cohort characteristics and clamp methodology (RISC to ULSAM: 0.491 [0.433, 0.539] for 51 proteins; ULSAM to RISC: 0.369 [0.331, 0.416] for 67 proteins). A randomised LASSO and stability selection algorithm selected only two proteins per cohort (three unique proteins), which improved R2 but to a lesser degree than in standard LASSO models: 0.352 (0.266, 0.439) in RISC and 0.495 (0.404, 0.585) in ULSAM. Reductions in improvements of R2 with randomised LASSO and stability selection were less marked in cross-cohort analyses (RISC to ULSAM R2 0.444 [0.391, 0.497]; ULSAM to RISC R2 0.348 [0.300, 0.396]). Models of proteins alone were as effective as models that included both clinical variables and proteins using either standard or randomised LASSO. The single most consistently selected protein across all analyses and models was IGF-binding protein 2. CONCLUSIONS/INTERPRETATION: A plasma proteomic signature identified using a standard LASSO approach improves the cross-sectional estimation of the M value over routine clinical variables. However, a small subset of these proteins identified using a stability selection algorithm affords much of this improvement, especially when considering cross-cohort analyses. Our approach provides opportunities to improve the identification of insulin-resistant individuals at risk of insulin resistance-related adverse health consequences.

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models.

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on human and mouse adipogenesis, as well as on cell-to-cell variability in gene expression during this process.

Contemporary Homozygous Familial Hypercholesterolemia in the United States: Insights From the CASCADE FH Registry.

Background Homozygous familial hypercholesterolemia (HoFH) is a rare, treatment-resistant disorder characterized by early-onset atherosclerotic and aortic valvular cardiovascular disease if left untreated. Contemporary information on HoFH in the United States is lacking, and the extent of underdiagnosis and undertreatment is uncertain. Methods and Results Data were analyzed from 67 children and adults with clinically diagnosed HoFH from the CASCADE (Cascade Screening for Awareness and Detection) FH Registry. Genetic diagnosis was confirmed in 43 patients. We used the clinical characteristics of genetically confirmed patients with HoFH to query the Family Heart Database, a US anonymized payer health database, to estimate the number of patients with similar lipid profiles in a "real-world" setting. Untreated low-density lipoprotein cholesterol levels were lower in adults than children (533 versus 776 mg/dL; P=0.001). At enrollment, atherosclerotic cardiovascular disease and supravalvular and aortic valve stenosis were present in 78.4% and 43.8% and 25.5% and 18.8% of adults and children, respectively. At most recent follow-up, despite multiple lipid-lowering treatment, low-density lipoprotein cholesterol goals were achieved in only a minority of adults and children. Query of the Family Heart Database identified 277 individuals with profiles similar to patients with genetically confirmed HoFH. Advanced lipid-lowering treatments were prescribed for 18%; 40% were on no lipid-lowering treatment; atherosclerotic cardiovascular disease was reported in 20%; familial hypercholesterolemia diagnosis was uncommon. Conclusions Only patients with the most severe HoFH phenotypes are diagnosed early. HoFH remains challenging to treat. Results from the Family Heart Database indicate HoFH is systemically underdiagnosed and undertreated. Earlier screening, aggressive lipid-lowering treatments, and guideline implementation are required to reduce disease burden in HoFH.

The relationship between insulin resistance and ion mobility lipoprotein fractions.

Objective: Insulin resistance (IR) increases risk of type 2 diabetes and atherosclerotic cardiovascular disease and is associated with lipid and lipoprotein abnormalities including high triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C). Lipoprotein size and lipoprotein subfractions (LS) have also been used to assist in identifying persons with IR. Associations of LS and IR have not been validated using both direct measures of IR and direct measures of LS. We assessed the usefulness of fasting lipoprotein subfractions (LS) by ion mobility to identify individuals with IR. Methods: Lipid panel, LS by ion mobility (LS-IM), and IR by steady-state plasma glucose (SSPG) concentration were assessed in 526 adult volunteers without diabetes. IR was defined as being in the highest tertile of SSPG concentration. LS-IM score was calculated by linear combination of regression coefficients from a stepwise regression analysis with SSPG concentration as the dependent variable. Improvement in prediction of IR was evaluated after combining LS-IM score with TG/HDL-C, TG/HDL-C and BMI as well as with TG/HDL-C, BMI, sex, race and ethnicity. IR prediction was evaluated by area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV) considering the highest 5% of scores as positive test. Results: Prediction of IR was similar by LS-IM score and TG/HDL-C (AUC=0.68; PPV=0.59 and AUC=0.70; PPV=0.59, respectively) and prediction was improved when LS-IM was combined with TG/HDL-C (AUC=0.73; PPV=0.70), TG/HDL-C and BMI (AUC=0.82; PPV=0.81) and with TG/HDL-C, BMI, sex, race and ethnicity (AUC=0.84; PPV=0.89). Conclusion: For identifying individuals with IR, LS-IM score and TG/HDL-C are comparable and their combination further improves IR prediction by TG/HDL-C alone. Among patients who have undergone IM testing, the LS-IM score may assist prioritization of subjects for further evaluation and interventions to reduce IR.

Chronic liver disease-related mortality in diabetes before and during the COVID-19 in the United States.

BACKGROUND: Global pandemic of COVID-19 represents an unprecedented challenge. COVID-19 has predominantly targeted vulnerable populations with pre-existing chronic medical diseases, such as diabetes and chronic liver disease. AIMS: We estimated chronic liver disease-related mortality trends among individuals with diabetes before and during the COVID-19 pandemic. METHODS: Utilizing the US national mortality database and Census, we determined the quarterly age-standardized chronic liver disease-related mortality and quarterly percentage change (QPC) among individuals with diabetes. RESULTS: The quarterly age-standardized mortality for chronic liver disease and/or cirrhosis among individuals with diabetes remained stable before the COVID-19 pandemic and sharply increased during the COIVD-19 pandemic at a QPC of 8.5%. The quarterly mortality from nonalcoholic fatty liver disease (NAFLD) and alcohol-related liver disease (ALD) increased markedly during the COVID-19 pandemic. Mortality for hepatitis C virus (HCV) infection declined with a quarterly rate of -3.3% before the COVID-19 pandemic and remained stable during the COVID-19 pandemic. While ALD- and HCV-related mortality was higher in men than in women, NAFLD-related mortality in women was higher than in men. CONCLUSIONS: The sharp increase in mortality for chronic liver disease and/or cirrhosis among individuals with diabetes during the COVID-19 pandemic was associated with increased mortality from NAFLD and ALD.