A genome-first approach to variants in MLXIPL and their association with hepatic steatosis and plasma lipids.

BACKGROUND: Common variants of the max-like protein X (MLX)-interacting protein-like (MLXIPL) gene, encoding the transcription factor carbohydrate-responsive element-binding protein, have been shown to be associated with plasma triglyceride levels. However, the role of these variants in steatotic liver disease (SLD) is unclear. METHODS: We used a genome-first approach to analyze a variety of metabolic phenotypes and clinical outcomes associated with a common missense variant in MLXIPL, Gln241His, in 2 large biobanks: the UK Biobank and the Penn Medicine Biobank. RESULTS: Carriers of MLXIPL Gln241His were associated with significantly lower serum levels of triglycerides, apolipoprotein-B, gamma-glutamyl transferase, and alkaline phosphatase. Additionally, MLXIPL Gln241His carriers were associated with significantly higher serum levels of HDL cholesterol and alanine aminotransferase. Carriers homozygous for MLXIPL Gln241His showed a higher risk of SLD in 2 unrelated cohorts. Carriers of MLXIPL Gln241His were especially more likely to be diagnosed with SLD if they were female, obese, and/or also carried the PNPLA3 I148M variant. Furthermore, the heterozygous carriage of MLXIPL Gln241His was associated with significantly higher all-cause, liver-related, and cardiovascular mortality rates. Nuclear magnetic resonance metabolomics data indicated that carriage of MLXIPL Gln241His was significantly associated with lower serum levels of VLDL and increased serum levels of HDL cholesterol. CONCLUSIONS: Analyses of the MLXIPL Gln241His polymorphism showed a significant association with a higher risk of SLD diagnosis and elevated serum alanine aminotransferase as well as significantly lower serum triglycerides and apolipoprotein-B levels. MLXIPL might, therefore, be a potential pharmacological target for the treatment of SLD and hyperlipidemia, notably for patients at risk. More mechanistic studies are needed to better understand the role of MLXIPL Gln241His on lipid metabolism and steatosis development.

Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP).

OBJECTIVE: To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. RESEARCH DESIGN AND METHODS: Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). RESULTS: T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥ 90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and they resembled T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. CONCLUSIONS: Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.

Integrative common and rare variant analyses provide insights into the genetic architecture of liver cirrhosis.

We report a multi-ancestry genome-wide association study on liver cirrhosis and its associated endophenotypes, alanine aminotransferase (ALT) and γ-glutamyl transferase. Using data from 12 cohorts, including 18,265 cases with cirrhosis, 1,782,047 controls, up to 1 million individuals with liver function tests and a validation cohort of 21,689 cases and 617,729 controls, we identify and validate 14 risk associations for cirrhosis. Many variants are located near genes involved in hepatic lipid metabolism. One of these, PNPLA3 p.Ile148Met, interacts with alcohol intake, obesity and diabetes on the risk of cirrhosis and hepatocellular carcinoma (HCC). We develop a polygenic risk score that associates with the progression from cirrhosis to HCC. By focusing on prioritized genes from common variant analyses, we find that rare coding variants in GPAM associate with lower ALT, supporting GPAM as a potential target for therapeutic inhibition. In conclusion, this study provides insights into the genetic underpinnings of cirrhosis.

Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis.

The objective of this study is to define CT imaging derived phenotypes for patients with hepatic steatosis, a common metabolic liver condition, and determine its association with patient data from a medical biobank. There is a need to further characterize hepatic steatosis in lean patients, as its epidemiology may differ from that in overweight patients. A deep learning method determined the spleen-hepatic attenuation difference (SHAD) in Hounsfield Units (HU) on abdominal CT scans as a quantitative measure of hepatic steatosis. The patient cohort was stratified by BMI with a threshold of 25 kg/m2 and hepatic steatosis with threshold SHAD ≥ - 1 HU or liver mean attenuation ≤ 40 HU. Patient characteristics, diagnoses, and laboratory results representing metabolism and liver function were investigated. A phenome-wide association study (PheWAS) was performed for the statistical interaction between SHAD and the binary characteristic LEAN. The cohort contained 8914 patients-lean patients with (N = 278, 3.1%) and without (N = 1867, 20.9%) steatosis, and overweight patients with (N = 1863, 20.9%) and without (N = 4906, 55.0%) steatosis. Among all lean patients, those with steatosis had increased rates of cardiovascular disease (41.7 vs 27.8%), hypertension (86.7 vs 49.8%), and type 2 diabetes mellitus (29.1 vs 15.7%) (all p < 0.0001). Ten phenotypes were significant in the PheWAS, including chronic kidney disease, renal failure, and cardiovascular disease. Hepatic steatosis was found to be associated with cardiovascular, kidney, and metabolic conditions, separate from overweight BMI.

A missense variant in human perilipin 2 (PLIN2 Ser251Pro) reduces hepatic steatosis in mice.

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is characterised by the accumulation of lipid droplets (LDs) within hepatocytes. Perilipin 2 (PLIN2) is the most abundant protein in hepatic LDs and its expression correlates with intracellular lipid accumulation. A recently discovered PLIN2 coding variant, Ser251Pro (rs35568725), was found to promote the accumulation of small LDs in embryonic kidney cells. In this study, we investigate the role of PLIN2-Ser251Pro (PLIN2-Pro251) on hepatic LD metabolism in vivo and research the metabolic phenotypes associated with this variant in humans. Methods: For our animal model, we used Plin2 knockout mice in which we expressed either human PLIN2-Pro251 (Pro251 mice) or wild-type human PLIN2-Ser251 (Ser251 mice) in a hepatocyte-specific manner. We fed both cohorts a lipogenic high-fat, high-cholesterol, high-fructose diet for 12 weeks. Results: Pro251 mice were associated with reduced liver triglycerides (TGs) and had lower mRNA expression of fatty acid synthase and diacylglycerol O-acyltransferase-2 compared with Ser251 mice. Moreover, Pro251 mice had a reduction of polyunsaturated fatty acids-TGs and reduced expression of epoxygenase genes. For our human study, we analysed the Penn Medicine BioBank, the Million Veteran Program, and UK Biobank. Across these databases, the minor allele frequency of PLIN2-Pro251 was approximately 5%. There was no association with the clinical diagnosis of NAFLD, however, there was a trend toward reduced liver fat in PLIN2-Pro251 carriers by MRI-spectroscopy in UK Biobank subjects. Conclusions: In mice lacking endogenous Plin2, expression of human PLIN2-Pro251 attenuated high-fat, high-fructose, high-cholesterol, diet-induced hepatic steatosis compared with human wild-type PLIN2-Ser251. Moreover, Pro251 mice had lower polyunsaturated fatty acids-TGs and epoxygenase genes expression, suggesting less liver oxidative stress. In humans, PLIN2-Pro251 is not associated with NAFLD. Impact and Implications: Lipid droplet accumulation in hepatocytes is the distinctive characteristic of non-alcoholic fatty liver disease. Perilipin 2 (PLIN2) is the most abundant protein in hepatic lipid droplets; however, little is known on the role of a specific polymorphism PLIN2-Pro251 on hepatic lipid droplet metabolism. PLIN2-Pro251 attenuates liver triglycerides accumulation after a high-fat-high-glucose-diet. PLIN2-Pro251 may be a novel lipid droplet protein target for the treatment of liver steatosis.

Session Introduction: Drug-repurposing and discovery in the era of "big" real-world data: how the incorporation of observational data, genetics, and other -omic technologies can move us forward.

This PSB 2024 session discusses the many broad biological, computational, and statistical approaches currently being used for therapeutic drug target identification and repurposing of existing treatments. Drug repurposing efforts have the potential to dramatically improve the treatment landscape by more rapidly identifying drug targets and alternative strategies for untreated or poorly managed diseases. The overarching theme for this session is the use and integration of real-world data to identify drug-disease pairs with potential therapeutic use. These drug-disease pairs may be identified through genomic, proteomic, biomarkers, protein interaction analyses, electronic health records, and chemical profiling. Taken together, this session combines novel applications of methods and innovative modeling strategies with diverse real-world data to suggest new pharmaceutical treatments for human diseases.

Profiling the genome and proteome of metabolic dysfunction-associated steatotic liver disease identifies potential therapeutic targets.

BACKGROUND & AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects over 25% of the population and currently has no effective treatments. Plasma proteins with causal evidence may represent promising drug targets. We aimed to identify plasma proteins in the causal pathway of MASLD and explore their interaction with obesity. METHODS: We analysed 2,941 plasma proteins in 43,978 European participants from UK Biobank. We performed genome-wide association study (GWAS) for all MASLD-associated proteins and created the largest MASLD GWAS (109,885 cases/1,014,923 controls). We performed Mendelian Randomization (MR) and integrated proteins and their encoding genes in MASLD ranges to identify candidate causal proteins. We then validated them through independent replication, exome sequencing, liver imaging, bulk and single-cell gene expression, liver biopsies, pathway, and phenome-wide data. We explored the role of obesity by MR and multivariable MR across proteins, body mass index, and MASLD. RESULTS: We found 929 proteins associated with MASLD, reported five novel genetic loci associated with MASLD, and identified 17 candidate MASLD protein targets. We identified four novel targets for MASLD (CD33, GRHPR, HMOX2, and SCG3), provided protein evidence supporting roles of AHCY, FCGR2B, ORM1, and RBKS in MASLD, and validated nine previously known targets. We found that CD33, FCGR2B, ORM1, RBKS, and SCG3 mediated the association of obesity and MASLD, and HMOX2, ORM1, and RBKS had effect on MASLD independent of obesity. CONCLUSIONS: This study identified new protein targets in the causal pathway of MASLD, providing new insights into the multi-omics architecture and pathophysiology of MASLD. These findings advise further therapeutic interventions for MASLD.

Aspirin is associated with a reduced incidence of liver disease in men.

BACKGROUND: The hepatoprotective effects of aspirin have been observed in individuals with viral hepatitis; however, its impact on the general population remains uncertain. Understanding the association between aspirin use and the development of liver diseases is crucial for optimizing preventive strategies. METHODS: We identified individuals with aspirin use in the UK Biobank and the Penn Medicine Biobank, as well as propensity-score-matched controls. Outcome measures included new liver disease development, diagnosed by MRI or "International Classification of Diseases and Related Health Problems" coding, and incidences of gastrointestinal bleeding and ulcers. RESULTS: In the UK Biobank cohort, regular aspirin use was associated with an 11.2% reduction in the risk of developing new liver diseases during the average 11.84 ± 2.01-year follow-up period (HR=0.888, 95% CI = 0.819-0.963; p = 4.1 × 10-3). Notably, the risk of metabolic dysfunction-associated steatotic liver disease (ICD-10 K76.0) and MRI-diagnosed steatosis was significantly lower among aspirin users (HR = 0.882-0.911), whereas no increased risk of gastrointestinal bleeding or ulcers was observed. These findings were replicated in the Penn Medicine Biobank cohort, in which the protective effect of aspirin appeared to be dependent on the duration of intake. The greatest risk reduction for new liver disease development was observed after at least 1 year of aspirin use (HR = 0.569, 95% CI = 0.425-0.762; p = 1.6 × 10-4). Intriguingly, when considering general risk factors, only men exhibited a lower risk of MRI-confirmed or ICD-coded steatosis with aspirin use (HRs = 0.806-0.906), while no significant protective effect of aspirin was observed in females. CONCLUSION: This cohort study demonstrated that regular aspirin use was associated with a reduced risk of liver disease in men without an elevated risk of gastrointestinal bleeding or ulcers. Further investigation is warranted to elucidate potential sex-related differences in the effects of aspirin and to inform tailored preventive strategies for liver diseases.

Large-scale identification of undiagnosed hepatic steatosis using natural language processing.

Background: Nonalcoholic fatty liver disease (NAFLD) is a major cause of liver-related morbidity in people with and without diabetes, but it is underdiagnosed, posing challenges for research and clinical management. Here, we determine if natural language processing (NLP) of data in the electronic health record (EHR) could identify undiagnosed patients with hepatic steatosis based on pathology and radiology reports. Methods: A rule-based NLP algorithm was built using a Linguamatics literature text mining tool to search 2.15 million pathology report and 2.7 million imaging reports in the Penn Medicine EHR from November 2014, through December 2020, for evidence of hepatic steatosis. For quality control, two independent physicians manually reviewed randomly chosen biopsy and imaging reports (n = 353, PPV 99.7%). Findings: After exclusion of individuals with other causes of hepatic steatosis, 3007 patients with biopsy-proven NAFLD and 42,083 patients with imaging-proven NAFLD were identified. Interestingly, elevated ALT was not a sensitive predictor of the presence of steatosis, and only half of the biopsied patients with steatosis ever received an ICD diagnosis code for the presence of NAFLD/NASH. There was a robust association for PNPLA3 and TM6SF2 risk alleles and steatosis identified by NLP. We identified 234 disorders that were significantly over- or underrepresented in all subjects with steatosis and identified changes in serum markers (e.g., GGT) associated with presence of steatosis. Interpretation: This study demonstrates clear feasibility of NLP-based approaches to identify patients whose steatosis was indicated in imaging and pathology reports within a large healthcare system and uncovers undercoding of NAFLD in the general population. Identification of patients at risk could link them to improved care and outcomes. Funding: The study was funded by US and German funding sources that did provide financial support only and had no influence or control over the research process.

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records.

BACKGROUND: The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery. METHODS: We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR). FINDINGS: After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p = 0.01 and -0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10-25). INTERPRETATION: Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions. FUNDING: National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program.

Mendelian randomization study of diabetes and dementia in the Million Veteran Program.

INTRODUCTION: Diabetes and dementia are diseases of high health-care burden worldwide. Individuals with diabetes have 1.4 to 2.2 times higher risk of dementia. Our objective was to evaluate evidence of causality between these two common diseases. METHODS: We conducted a one-sample Mendelian randomization (MR) analysis in the US Department of Veterans Affairs Million Veteran program. The study included 334,672 participants ≥65 years of age with type 2 diabetes and dementia case-control status and genotype data. RESULTS: For each standard deviation increase in genetically predicted diabetes, we found increased odds of three dementia diagnoses in non-Hispanic White participants (all-cause: odds ratio [OR] = 1.07 [1.05-1.08], P = 3.40E-18; vascular: OR = 1.11 [1.07-1.15], P = 3.63E-09, Alzheimer's disease [AD]: OR = 1.06 [1.02-1.09], P = 6.84E-04) and non-Hispanic Black participants (all-cause: OR = 1.06 [1.02-1.10], P = 3.66E-03, vascular: OR = 1.11 [1.04-1.19], P = 2.20E-03, AD: OR = 1.12 [1.02-1.23], P = 1.60E-02) but not in Hispanic participants (all P > 0.05). DISCUSSION: We found evidence of causality between diabetes and dementia using a one-sample MR study, with access to individual level data, overcoming limitations of prior studies using two-sample MR techniques.

Genetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample.

OBJECTIVE: Recent genome-wide association studies (GWASs) of alcohol-related phenotypes have uncovered key differences in the underlying genetic architectures of alcohol consumption and alcohol use disorder (AUD), with the two traits having opposite genetic correlations with psychiatric disorders. Understanding the genetic factors that underlie the transition from heavy drinking to AUD has important theoretical and clinical implications. METHODS: The authors used longitudinal data from the cross-ancestry Million Veteran Program sample to identify 1) novel loci associated with AUD and alcohol consumption (measured by the score on the consumption subscale of the Alcohol Use Disorders Identification Test [AUDIT-C]), 2) the impact of phenotypic variation on genetic discovery, and 3) genetic variants with direct effects on AUD that are not mediated through alcohol consumption. RESULTS: The authors identified 26 loci associated with AUD and 22 loci associated with AUDIT-C score, including ancestry-specific and novel loci. In secondary GWASs that excluded individuals who report abstinence, the authors identified seven additional loci for AUD and eight additional loci for AUDIT-C score. Although the heterogeneity of the abstinent group biases the GWAS findings, unique variance between alcohol consumption and disorder remained after the abstinent group was excluded. Finally, using mediation analysis, the authors identified a set of variants with effects on AUD that are not mediated through alcohol consumption. CONCLUSIONS: Differences in genetic architecture between alcohol consumption and AUD are consistent with their having different biological contributions. Genetic variants with direct effects on AUD are potentially relevant to understanding the transition from heavy alcohol consumption to AUD and may be targets for translational prevention and treatment efforts.

Association of Statin Use With Risk of Liver Disease, Hepatocellular Carcinoma, and Liver-Related Mortality.

Importance: Given the burden of chronic liver disease on the health care system, more information on the hepatoprotective association of statins in the general population is needed. Objective: To examine whether regular statin use is associated with a reduction in liver disease, particularly hepatocellular carcinoma (HCC) and liver-related deaths, in the general population. Design, Setting, and Participants: This cohort study used data from the UK Biobank (UKB) (individuals aged 37-73 years) collected from baseline (2006-2010) to the end of follow-up in May 2021, from the TriNetX cohort (individuals aged 18-90 years) enrolled from baseline (2011-2020) until end of follow-up in September 2022, and from the Penn Medicine Biobank (PMBB) (individuals aged 18-102 years) with ongoing enrollment starting in 2013 to the end of follow-up in December 2020. Individuals were matched using propensity score matching according to the following criteria: age, sex, body mass index, ethnicity, diabetes with or without insulin or biguanide use, hypertension, ischemic heart disease, dyslipidemia, aspirin use, and number of medications taken (UKB only). Data analysis was performed from April 2021 to April 2023. Exposure: Regular statin use. Main Outcomes and Measures: Primary outcomes were liver disease and HCC development as well as liver-associated death. Results: A total of 1 785 491 individuals were evaluated after matching (aged 55 to 61 years on average, up to 56% men, and up to 49% women). A total of 581 cases of liver-associated death, 472 cases of incident HCC, and 98 497 new liver diseases were registered during the follow-up period. Individuals were aged 55-61 years on average, with a slightly higher proportion of men (up to 56%). In UKB individuals (n = 205 057) without previously diagnosed liver disease, statin users (n = 56 109) had a 15% lower hazard ratio (HR) for the association of developing a new liver disease (HR, 0.85; 95% CI, 0.78-0.92; P < .001). In addition, statin users demonstrated a 28% lower HR for the association with liver-related death (HR, 0.72; 95% CI, 0.59-0.88; P = .001) and a 42% lower HR for the development of HCC (HR, 0.58; 95% CI, 0.35-0.96; P = .04). In TriNetX individuals (n = 1 568 794), the HR for the association of HCC was reduced even further for statin users (HR, 0.26; 95% CI, 0.22-0.31; P = .003). The hepatoprotective association of statins was time and dose dependent, with a significant association in PMBB individuals (n = 11 640) for incident liver diseases after 1 year of statin use (HR, 0.76; 95% CI, 0.59-0.98; P = .03). Taking statins was particularly beneficial in men, individuals with diabetes, and individuals with a high Fibrosis-4 index at baseline. Carriers of the heterozygous minor allele of PNPLA3 rs738409 benefited from statin use and had a 69% lower HR for the association with HCC (UKB HR, 0.31; 95% CI, 0.11-0.85; P = .02). Conclusions and Relevance: This cohort study indicates substantial preventive associations of statins against liver disease, with an association with duration and dose of intake.

Genetically proxied glucose-lowering drug target perturbation and risk of cancer: a Mendelian randomisation analysis.

AIMS/HYPOTHESIS: Epidemiological studies have generated conflicting findings on the relationship between glucose-lowering medication use and cancer risk. Naturally occurring variation in genes encoding glucose-lowering drug targets can be used to investigate the effect of their pharmacological perturbation on cancer risk. METHODS: We developed genetic instruments for three glucose-lowering drug targets (peroxisome proliferator activated receptor γ [PPARG]; sulfonylurea receptor 1 [ATP binding cassette subfamily C member 8 (ABCC8)]; glucagon-like peptide 1 receptor [GLP1R]) using summary genetic association data from a genome-wide association study of type 2 diabetes in 148,726 cases and 965,732 controls in the Million Veteran Program. Genetic instruments were constructed using cis-acting genome-wide significant (p<5×10-8) SNPs permitted to be in weak linkage disequilibrium (r2<0.20). Summary genetic association estimates for these SNPs were obtained from genome-wide association study (GWAS) consortia for the following cancers: breast (122,977 cases, 105,974 controls); colorectal (58,221 cases, 67,694 controls); prostate (79,148 cases, 61,106 controls); and overall (i.e. site-combined) cancer (27,483 cases, 372,016 controls). Inverse-variance weighted random-effects models adjusting for linkage disequilibrium were employed to estimate causal associations between genetically proxied drug target perturbation and cancer risk. Co-localisation analysis was employed to examine robustness of findings to violations of Mendelian randomisation (MR) assumptions. A Bonferroni correction was employed as a heuristic to define associations from MR analyses as 'strong' and 'weak' evidence. RESULTS: In MR analysis, genetically proxied PPARG perturbation was weakly associated with higher risk of prostate cancer (for PPARG perturbation equivalent to a 1 unit decrease in inverse rank normal transformed HbA1c: OR 1.75 [95% CI 1.07, 2.85], p=0.02). In histological subtype-stratified analyses, genetically proxied PPARG perturbation was weakly associated with lower risk of oestrogen receptor-positive breast cancer (OR 0.57 [95% CI 0.38, 0.85], p=6.45×10-3). In co-localisation analysis, however, there was little evidence of shared causal variants for type 2 diabetes liability and cancer endpoints in the PPARG locus, although these analyses were likely underpowered. There was little evidence to support associations between genetically proxied PPARG perturbation and colorectal or overall cancer risk or between genetically proxied ABCC8 or GLP1R perturbation with risk across cancer endpoints. CONCLUSIONS/INTERPRETATION: Our drug target MR analyses did not find consistent evidence to support an association of genetically proxied PPARG, ABCC8 or GLP1R perturbation with breast, colorectal, prostate or overall cancer risk. Further evaluation of these drug targets using alternative molecular epidemiological approaches may help to further corroborate the findings presented in this analysis. DATA AVAILABILITY: Summary genetic association data for select cancer endpoints were obtained from the public domain: breast cancer ( https://bcac.ccge.medschl.cam.ac.uk/bcacdata/ ); and overall prostate cancer ( http://practical.icr.ac.uk/blog/ ). Summary genetic association data for colorectal cancer can be accessed by contacting GECCO (kafdem at fredhutch.org). Summary genetic association data on advanced prostate cancer can be accessed by contacting PRACTICAL (practical at icr.ac.uk). Summary genetic association data on type 2 diabetes from Vujkovic et al (Nat Genet, 2020) can be accessed through dbGAP under accession number phs001672.v3.p1 (pha004945.1 refers to the European-specific summary statistics). UK Biobank data can be accessed by registering with UK Biobank and completing the registration form in the Access Management System (AMS) ( https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access ).

A coding variant in the microsomal triglyceride transfer protein reduces both hepatic steatosis and plasma lipids.

BACKGROUND: Genetic inactivation and pharmacologic inhibition of the microsomal triglyceride transfer protein (MTP; gene name MTTP) inhibits hepatic secretion of VLDL, thereby reducing serum lipids and apoB at the expense of increasing hepatic steatosis. AIM: To examine the effects of missense variants in MTTP on hepatic and circulating lipids. METHODS: We analysed the association of MTTP missense variants with metabolic, hepatic and clinical phenotypes in the Penn Medicine Biobank (PMBB; n = 37,960) and the UKBiobank (UKB; n = 451,444). RESULTS: We analysed 24 missense variants in MTTP in PMBB for association with biopsy-proven hepatic steatosis and found that an isoleucine 128 to threonine variant (I128T: rs3816873-A, frequency 26%) was associated with reduced steatosis (p < 0.001). PMBB subjects with imaging-proven steatosis also revealed significantly fewer carriers of MTTP I128T compared to controls. Analysis in UKB also showed that MTTP I128T was associated with reduced risk of hepatic steatosis. Unexpectedly, MTTP I128T was found to be associated with reduced plasma levels of LDL-cholesterol and apoB (all p < 0.001). Functional studies indicated that MTTP I128T is neither a classic loss nor gain of function allele. CONCLUSIONS: MTTP I128T is associated with reduced hepatic steatosis as well as reduced plasma lipids and apoB. This paradoxical profile is not consistent with a simple gain or loss of function in MTP activity and suggests a more complex effect on MTP function. Further investigation of MTTP I128T will provide insight into the structure-function of MTP and potentially new approaches to modulate MTP activity that could both reduce hepatic and circulating lipids.

Mendelian randomization study of diabetes and dementia in the Million Veteran Program.

INTRODUCTION: Diabetes and dementia are diseases of high healthcare burden worldwide. Individuals with diabetes have 1.4 to 2.2 times higher risk of dementia. Our objective was to evaluate evidence of causality between these two common diseases. METHODS: We conducted a one-sample Mendelian randomization (MR) analysis in the U.S. Department of Veterans Affairs Million Veteran program. The study included 334,672 participants ≥65 years of age with type 2 diabetes and dementia case-control status and genotype data. RESULTS: For each standard deviation increase in genetically-predicted diabetes, we found increased odds of three dementia diagnoses in non-Hispanic White participants (all-cause: OR=1.07[1.05-1.08], P =3.40E-18; vascular: OR=1.11[1.07-1.15], P =3.63E-09, Alzheimer's: OR=1.06[1.02-1.09], P =6.84E-04) and non-Hispanic Black participants (all-cause: OR=1.06[1.02-1.10], P =3.66E-03, vascular: OR=1.11[1.04-1.19], P =2.20E-03, Alzheimer's: OR=1.12 [1.02-1.23], P =1.60E-02) but not in Hispanic participants (all P >.05). DISCUSSION: We found evidence of causality between diabetes and dementia using a one-sample MR study, with access to individual level data, overcoming limitations of prior studies utilizing two-sample MR techniques.

Comparison of the structure-function properties of wild-type human apoA-V and a C-terminal truncation associated with elevated plasma triglycerides.

Background: Plasma triglycerides (TGs) are causally associated with coronary artery disease and acute pancreatitis. Apolipoprotein A-V (apoA-V, gene APOA5) is a liver-secreted protein that is carried on triglyceride-rich lipoproteins and promotes the enzymatic activity of lipoprotein lipase (LPL), thereby reducing TG levels. Little is known about apoA-V structure-function; naturally occurring human APOA5 variants can provide novel insights. Methods: We used hydrogen-deuterium exchange mass spectrometry to determine the secondary structure of human apoA-V in lipid-free and lipid-associated conditions and identified a C-terminal hydrophobic face. Then, we used genomic data in the Penn Medicine Biobank to identify a rare variant, Q252X, predicted to specifically eliminate this region. We interrogated the function of apoA-V Q252X using recombinant protein in vitro and in vivo in apoa5 knockout mice. Results: Human apoA-V Q252X carriers exhibited elevated plasma TG levels consistent with loss of function. Apoa5 knockout mice injected with AAV vectors expressing wildtype and variant APOA5-AAV recapitulated this phenotype. Part of the loss of function is due to reduced mRNA expression. Functionally, recombinant apoA-V Q252X was more readily soluble in aqueous solutions and more exchangeable with lipoproteins than WT apoA-V. Despite lacking the C-terminal hydrophobic region (a putative lipid binding domain) this protein also decreased plasma TG in vivo. Conclusions: Deletion of apoA-V's C-terminus leads to reduced apoA-V bioavailability in vivo and higher TG levels. However, the C-terminus is not required for lipoprotein binding or enhancement of intravascular lipolytic activity. WT apoA-V is highly prone to aggregation, and this property is markedly reduced in recombinant apoA-V lacking the C-terminus.

Session Introduction: SALUD: Scalable Applications of cLinical risk Utility and preDiction.

This PSB 2023 session discusses challenges in clinical implication and application of risk prediction models, which includes but is not limited to: implementation of risk models, responsible use of polygenic risk scores (PGS), and other risk prediction strategies. We focus on the development and use of new, scalable methods for harmonizing and refining risk prediction models by incorporating genetic and non-genetic risk factors, applying new phenotyping strategies, and integrating clinical factors and biomarkers. Lastly, we will discuss innovation in expanding the utility of these prediction models to underrepresented populations. This session focuses on the overarching theme of enabling early diagnosis, and treatment and preventive measures related to complex diseases and comorbidities.

Genomics and phenomics of body mass index reveals a complex disease network.

Elevated body mass index (BMI) is heritable and associated with many health conditions that impact morbidity and mortality. The study of the genetic association of BMI across a broad range of common disease conditions offers the opportunity to extend current knowledge regarding the breadth and depth of adiposity-related diseases. We identify 906 (364 novel) and 41 (6 novel) genome-wide significant loci for BMI among participants of European (N~1.1 million) and African (N~100,000) ancestry, respectively. Using a BMI genetic risk score including 2446 variants, 316 diagnoses are associated in the Million Veteran Program, with 96.5% showing increased risk. A co-morbidity network analysis reveals seven disease communities containing multiple interconnected diseases associated with BMI as well as extensive connections across communities. Mendelian randomization analysis confirms numerous phenotypes across a breadth of organ systems, including conditions of the circulatory (heart failure, ischemic heart disease, atrial fibrillation), genitourinary (chronic renal failure), respiratory (respiratory failure, asthma), musculoskeletal and dermatologic systems that are deeply interconnected within and across the disease communities. This work shows that the complex genetic architecture of BMI associates with a broad range of major health conditions, supporting the need for comprehensive approaches to prevent and treat obesity.