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One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.

BackgroundThe US government considers veterans to have been exposed to Agent Orange if they served in Vietnam while the carcinogen was in use, and these veterans are often deemed at high risk of prostate cancer (PCa). Here, we assess whether presumed Agent Orange exposure is independently associated with increased risk of any metastatic or fatal PCa in a diverse Veteran cohort still alive in the modern era (at least 2011), when accounting for race/ethnicity, family history, and genetic risk.Patients and methodsParticipants in the Million Veteran Program (MVP; enrollment began in 2011) who were on active duty during the Vietnam War era (August 1964-April 1975) were included (n = 301,470). Agent Orange exposure was determined using the US government definition. Genetic risk was assessed via a validated polygenic hazard score. Associations with age at diagnosis of any PCa, metastatic PCa, and death from PCa were assessed via Cox proportional hazards models.Results and interpretationOn univariable analysis, exposure to Agent Orange was not associated with increased PCa (hazard ratio [HR]: 1.02, 95% confidence interval [CI]: 1.00-1.04, p = 0.06), metastatic PCa (HR: 0.98, 95% CI: 0.91-1.05, p = 0.55), or fatal PCa (HR: 0.94, 95% CI: 0.79-1.09, p = 0.41). When accounting for race/ethnicity and family history, Agent Orange exposure was independently associated with slightly increased risk of PCa (HR: 1.06, 95% CI: 1.04-1.09,

Background: Observational studies have reported strongly protective effects of bariatric surgery on cardiovascular disease, but with oversimplified definitions of the intervention, eligibility criteria, and follow-up, which deviate from those in a randomized trial. We describe an attempt to estimate the effect of bariatric surgery on cardiovascular disease without introducing these sources of bias, which may not be entirely possible with existing observational data. Methods: We propose two target trials among persons with diabetes: (1) bariatric operation (vs. no operation) among individuals who have undergone preoperative preparation (lifestyle modifications and screening) and (2) preoperative preparation and a bariatric operation (vs. neither preoperative nor operative component). We emulated both target trials using observational data of US veterans. Results: Comparing bariatric surgery with no surgery (target trial #1; 8,087 individuals), the 7-year cardiovascular risk was 18.0% (95% CI = 6.9, 32.7) in the surgery group and 18.9% (95% CI = 17.7, 20.1) in the no-surgery group (risk difference -0.9, 95% CI = -12.0, 14.0). Comparing preoperative components plus surgery vs. neither (target trial #2; 10,065 individuals), the 7-year cardiovascular risk was 17.4% (95% CI = 13.6, 22.0) in the surgery group and 18.8% (95% CI = 17.8, 19.9) in the no-surgery group (risk difference -1.4, 95% CI = -5.1, 3.2). Body mass index and hemoglobin A1c were reduced with bariatric interventions in both emulations. Conclusions: Within limitations of available observational data, our estimates do not provide evidence that bariatric surgery reduces cardiovascular disease and support equipoise for a randomized trial of bariatric surgery for cardiovascular disease prevention. [ABSTRACT FROM AUTHOR]

PURPOSE: Stage in multiple myeloma (MM) is an essential measure of disease risk, but its measurement in large databases is often lacking. We aimed to develop and validate a natural language processing (NLP) algorithm to extract oncologists' documentation of stage in the national Veterans Affairs (VA) Healthcare System. METHODS: Using nationwide electronic health record (EHR) and cancer registry data from the VA Corporate Data Warehouse, we developed and validated a rule-based NLP algorithm to extract oncologist-determined MM stage. To that end, a clinician annotated MM stage within over 5,000 short snippets of clinical notes, and annotated MM stage at MM treatment initiation for 200 patients. These were allocated into snippet- and patient-level development and validation sets. We developed MM stage extraction and roll-up algorithms within the development sets. After the algorithms were finalized, we validated them using standard measures in held-out validation sets. RESULTS: We developed algorithms for three different MM staging systems that have been in widespread use (Revised International Staging System [R-ISS], International Staging System [ISS], and Durie-Salmon [DS]) and for stage reported without a clearly defined system. Precision and recall were uniformly high for MM stage at the snippet level, ranging from 0.92 to 0.99 for the different MM staging systems. Performance in identifying for MM stage at treatment initiation at the patient level was also excellent, with precision of 0.92, 0.96, 0.90, and 0.86 and recall of 0.99, 0.98, 0.94, and 0.92 for R-ISS, ISS, DS, and unclear stage, respectively. CONCLUSION: Our MM stage extraction algorithm uses rule-based NLP and data aggregation to accurately measure MM stage documented in oncology notes and pathology reports in VA's national EHR system. It may be adapted to other systems where MM stage is recorded in clinical notes. Stage is a key factor in assessment of multiple myeloma (MM) risk, but large databases lack the necessary laboratory and pathology data for staging. We developed a rules-based NLP algorithm to extract oncologist-determined MM stage from VA EHR data. The algorithm demonstrated accurate assignment of MM stage when validated against clinician annotation. [ABSTRACT FROM AUTHOR]

Background: Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can complicate the detection of early signs of ADRD. The interplay between PTSD, head injury, subjective (self-reported) cognitive concerns and genetic risk for ADRD is also not well understood, particularly in diverse ancestry groups. Methods: Using data from the U.S. Department of Veterans Affairs (VA) Million Veteran Program (MVP), we examined the relationship between dementia risk factors (APOE ε4, PTSD, TBI) and subjective cognitive concerns (SCC) measured in individuals of European (n = 140,921), African (n = 15,788), and Hispanic (n = 8,064) ancestry (EA, AA, and HA, respectively). We then used data from the VA electronic medical record to perform a retrospective survival analysis evaluating PTSD, TBI, APOE ε4, and SCC and their associations with risk of conversion to ADRD in Veterans aged 65 and older. Results: PTSD symptoms (B = 0.50–0.52, p < 1E-250) and probable TBI (B = 0.05–0.19, p = 1.51E-07 – 0.002) were positively associated with SCC across all three ancestry groups. APOE ε4 was associated with greater SCC in EA Veterans aged 65 and older (B = 0.037, p = 1.88E-12). Results of Cox models indicated that PTSD symptoms (hazard ratio [HR] = 1.13–1.21), APOE ε4 (HR = 1.73–2.05) and SCC (HR = 1.18–1.37) were positively associated with risk for ADRD across all three ancestry groups. In the EA group, probable TBI also contributed to increased risk of ADRD (HR = 1.18). Conclusions: The findings underscore the value of SCC as an indicator of ADRD risk in Veterans 65 and older when considered in conjunction with other influential genetic, clinical, and demographic risk factors. [ABSTRACT FROM AUTHOR]

Background: Statins are part of long‐term medical regimens for many older adults. Whether frailty modifies the protective relationship between statins, mortality, and major adverse cardiovascular events (MACE) is unknown. Methods: This was a retrospective study of US Veterans ≥65, without CVD or prior statin use seen in 2002–2012, followed through 2017. A 31‐item frailty index was used. The co‐primary endpoint was all‐cause mortality or MACE (MI, stroke/TIA, revascularization, or cardiovascular death). Cox proportional hazards models were developed to evaluate the association of statin use with outcomes; propensity score overlap weighting accounted for confounding by indication. Results: We identified 710,313 Veterans (mean age (SD) 75.3(6.5), 98% male, 89% white); 86,327 (12.1%) were frail. Over mean follow‐up of 8 (5) years, there were 48.6 and 72.6 deaths per 1000 person‐years (PY) among non‐frail statin‐users vs nonusers (weighted Incidence Rate Difference (wIRD)/1000 person years (PY), −24.0[95% CI, −24.5 to −23.6]), and 90.4 and 130.4 deaths per 1000PY among frail statin‐users vs nonusers (wIRD/1000PY, −40.0[95% CI, −41.8 to −38.2]). There were 51.7 and 60.8 MACE per 1000PY among non‐frail statin‐users vs nonusers (wIRD/1000PY, −9.1[95% CI, −9.7 to −8.5]), and 88.2 and 102.0 MACE per 1000PY among frail statin‐users vs nonusers (wIRD/1000PY, −13.8[95% CI, −16.2 to −11.4]). There were no significant interactions by frailty for statin users vs non‐users by either mortality or MACE outcomes, p‐interaction 0.770 and 0.319, respectively. Statin use was associated with lower risk of all‐cause mortality (HR, 0.61 (0.60–0.61)) and MACE (HR 0.86 (0.85–0.87)). Conclusions: New statin use is associated with a lower risk of mortality and MACE, independent of frailty. These findings should be confirmed in a randomized clinical trial. See related editorial by Aliberti et al. in this issue. [ABSTRACT FROM AUTHOR]

Aims: We sought to identify factors associated with right ventricular (RV) dysfunction and elevated pulmonary artery systolic pressure (PASP) and association with adverse outcomes in peripartum cardiomyopathy (PPCM). Methods and results: We conducted a multi‐centre cohort study to identify subjects with PPCM with the following criteria: left ventricular ejection fraction (LVEF) < 40%, development of heart failure within the last month of pregnancy or 5 months of delivery, and no other identifiable cause of heart failure with reduced ejection fraction. Outcomes included a composite of (i) major adverse events (need for extracorporeal membrane oxygenation, ventricular assist device, orthotopic heart transplantation, or death) or (ii) recurrent heart failure hospitalization. RV function was obtained from echocardiogram reports. In total, 229 women (1993–2017) met criteria for PPCM. Mean age was 32.4 ± 6.8 years, 28% were of African descent, 50 (22%) had RV dysfunction, and 38 (17%) had PASP ≥ 30 mmHg. After a median follow‐up of 3.4 years (interquartile range 1.0–8.8), 58 (25%) experienced the composite outcome of adverse events. African descent, family history of cardiomyopathy, LVEF, and PASP were significant predictors of RV dysfunction. Using Cox proportional hazards models, we found that women with RV dysfunction were three times more likely to experience the adverse composite outcome: hazard ratio 3.21 (95% confidence interval: 1.11–9.28), P = 0.03, in a multivariable model adjusting for age, race, body mass index, preeclampsia, hypertension, diabetes, kidney disease, and LVEF. Women with PASP ≥ 30 mmHg had a lower probability of survival free from adverse events (log‐rank P = 0.04). Conclusions: African descent and family history of cardiomyopathy were significant predictors of RV dysfunction. RV dysfunction and elevated PASP were significantly associated with a composite of major adverse cardiac events. This at‐risk group may prompt closer monitoring or early referral for advanced therapies. [ABSTRACT FROM AUTHOR]

An editorial focuses on evaluating the potential for improving cardiovascular risk assessment by incorporating additional biomarkers into standard risk prediction models. It reviews a study which demonstrates modest but significant improvements in predicting cardiovascular events and mortality when biomarkers such as high-sensitivity cardiac troponin I, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein are added to traditional risk equations.

Importance: The X chromosome has remained enigmatic in Alzheimer disease (AD), yet it makes up 5% of the genome and carries a high proportion of genes expressed in the brain, making it particularly appealing as a potential source of unexplored genetic variation in AD., Objectives: To perform the first large-scale X chromosome-wide association study (XWAS) of AD., Design, Setting, and Participants: This was a meta-analysis of genetic association studies in case-control, family-based, population-based, and longitudinal AD-related cohorts from the US Alzheimer's Disease Genetics Consortium, the Alzheimer's Disease Sequencing Project, the UK Biobank, the Finnish health registry, and the US Million Veterans Program. Risk of AD was evaluated through case-control logistic regression analyses. Data were analyzed between January 2023 and March 2024. Genetic data available from high-density single-nucleotide variant microarrays and whole-genome sequencing and summary statistics for multitissue expression and protein quantitative trait loci available from published studies were included, enabling follow-up genetic colocalization analyses. A total of 1 629 863 eligible participants were selected from referred and volunteer samples, 477 596 of whom were excluded for analysis exclusion criteria. The number of participants who declined to participate in original studies was not available., Main Outcome and Measures: Risk of AD, reported as odds ratios (ORs) with 95% CIs. Associations were considered at X chromosome-wide (P < 1 × 10-5) and genome-wide (P < 5 × 10-8) significance. Primary analyses are nonstratified, while secondary analyses evaluate sex-stratified effects., Results: Analyses included 1 152 284 participants of non-Hispanic White, European ancestry (664 403 [57.7%] female and 487 881 [42.3%] male), including 138 558 individuals with AD. Six independent genetic loci passed X chromosome-wide significance, with 4 showing support for links between the genetic signal for AD and expression of nearby genes in brain and nonbrain tissues. One of these 4 loci passed conservative genome-wide significance, with its lead variant centered on an intron of SLC9A7 (OR, 1.03; 95% CI, 1.02-1.04) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes. Of these 6 loci, 4 displayed evidence for escape from X chromosome inactivation with regard to AD risk., Conclusion and Relevance: This large-scale XWAS of AD identified the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid β accumulation. Overall, this study advances our knowledge of AD genetics and may provide novel biological drug targets. The results further provide initial insights into elucidating the role of the X chromosome in sex-based differences in AD.

We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify novel genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. We collected data from 55 cohorts with a combined sample size of 732,564 participants (87% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for the one-degree of freedom tests of interaction and two-degree of freedom joint tests of the main and interaction effect. In the cross-population meta-analyses, the one-degree of freedom variant-sleep interaction test identified 10 loci (P int <5.0e-9) not previously observed for lipids. Of interest, the ASPH locus (TG, LTST) is a target for aspartic and succinic acid metabolism previously shown to improve sleep and cardiovascular risk. The two-degree of freedom analyses identified an additional 7 loci that showed evidence for variant-sleep interaction (P joint <5.0e-9 in combination with P int <6.6e-6). Of these, the SLC8A1 locus (TG, STST) has been considered a potential treatment target for reduction of ischemic damage after acute myocardial infarction. Collectively, the 17 (9 with STST; 8 with LTST) loci identified in this large-scale initiative provides evidence into the biomolecular mechanisms underpinning sleep-duration-associated changes in lipid levels. The identified druggable targets may contribute to the development of novel therapies for dyslipidemia in people with sleep disturbances.

Aims: Elevated Lipoprotein(a) [Lp(a)] is a causal risk factor for atherosclerotic cardiovascular disease, but the mechanisms of risk are debated. Studies have found inconsistent associations between Lp(a) and measurements of atherosclerosis. We aimed to assess the relationship between Lp(a), low-density lipoprotein cholesterol (LDL-C) and coronary artery plaque severity., Methods: The study population consisted of participants of the Million Veteran Program who have undergone an invasive angiogram. The primary exposure was genetically predicted Lp(a), estimated by a polygenic score. Genetically predicted LDL-C was also assessed for comparison. The primary outcome was coronary artery plaque severity, categorized as normal, non-obstructive disease, 1-vessel disease, 2-vessel disease, and 3-vessel or left main disease., Results: Among 18,927 adults of genetically inferred European ancestry and 4,039 adults of genetically inferred African ancestry, we observed consistent associations between genetically predicted Lp(a) and obstructive coronary plaque, with effect sizes trending upward for increasingly severe categories of disease. Associations were independent of risk factors, clinically measured LDL-C and genetically predicted LDL-C. However, we did not find strong or consistent evidence for an association between genetically predicted Lp(a) and risk for non-obstructive plaque., Conclusions: Genetically predicted Lp(a) is positively associated with coronary plaque severity independent of LDL-C, consistent with Lp(a) promoting atherogenesis. However, the effects of Lp(a) may be greater for progression of plaque to obstructive disease than for the initial development of non-obstructive plaque. A limitation of this study is that Lp(a) was estimated using genetic markers and could not be directly assayed, nor could apo(a) isoform size., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Vitamin D may prevent the development of hypertension through down-regulation of renin-angiotensin system. However, epidemiologic studies assessing the interrelation of vitamin D-related biomarkers with hypertension are sparse., Methods: We examined the prospective associations between vitamin D-related biomarkers and risk of hypertension in a nested case-control study. In each of the Women's Health Study (WHS) and Physicians' Health Study (PHS) II, 500 incident hypertension cases and 500 age and race matched controls were randomly selected. Baseline plasma 25(OH)-vitamin D [25(OH)D], parathyroid hormone (PTH), and total renin concentrations were measured., Results: Among controls, 25(OH)D and PTH were inversely correlated, but neither was correlated with total renin. In the crude model, there was a trend of association between increasing quintiles of 25(OH)D and lower risk of hypertension in women, with relative risks and 95% CIs of 1.00, 1.24 (0.84-1.83), 0.82 (0.53-1.25), 0.75 (0.48-1.16), and 0.81 (0.52-1.27) (p, trend: 0.07). Adjustment for body mass index and other hypertension risk factors eliminated this association (RR of 5th quintile: 1.03). No associations were found in men. Baseline PTH and ratio of 25(OH)D to PTH were not associated with risk of hypertension in women or men. When men and women were included in the same model, vitamin D insufficiency (defined as 25(OH)D <20 ng/mL) also was not associated with increased risk of hypertension. No interactions were found across subgroups., Conclusions: Our study found no association of baseline plasma 25(OH)D or PTH with risk of hypertension or total renin concentration in middle-aged and older men and women., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Journal of Hypertension, Ltd. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT)., Methods: We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies., Results: Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A , SCN10A , and TTN/CCDC141 . Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals., Conclusions: Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility., Competing Interests: Disclosures Dr Lubitz is a full-time employee of Novartis as of July 2022. Previously, Dr Lubitz received research support from Bristol Myers Squibb/Pfizer, Bayer AG, Boehringer Ingelheim, Fitbit, IBM, Medtronic, and Premier, Inc, and consulted for Bristol Myers Squibb/Pfizer, Bayer AG, Blackstone Life Sciences, and Invitae. Dr Ellinor receives research support from Bayer AG, IBM, and Bristol Myers Squibb/Pfizer and has consulted for Novartis, MyoKardia, and Bayer AG. Dr Damrauer receives research support for RenalytixAI and has consulted for Calico Labs. Dr Svendsen is a member of Medtronic advisory boards and has received speaker honoraria and research grants from Medtronic outside this work. Dr Cutler has consulted for Janssen Scientific. Dr Roselli is supported by a grant from Bayer AG to the Broad Institute focused on the development of therapeutics for cardiovascular disease. The other authors report no conflicts.

The expansion of biobanks has significantly propelled genomic discoveries yet the sheer scale of data within these repositories poses formidable computational hurdles, particularly in handling extensive matrix operations required by prevailing statistical frameworks. In this work, we introduce computational optimizations to the SAIGE (Scalable and Accurate Implementation of Generalized Mixed Model) algorithm, notably employing a GPU-based distributed computing approach to tackle these challenges. We applied these optimizations to conduct a large-scale genome-wide association study (GWAS) across 2,068 phenotypes derived from electronic health records of 635,969 diverse participants from the Veterans Affairs (VA) Million Veteran Program (MVP). Our strategies enabled scaling up the analysis to over 6,000 nodes on the Department of Energy (DOE) Oak Ridge Leadership Computing Facility (OLCF) Summit High-Performance Computer (HPC), resulting in a 20-fold acceleration compared to the baseline model. We also provide a Docker container with our optimizations that was successfully used on multiple cloud infrastructures on UK Biobank and All of Us datasets where we showed significant time and cost benefits over the baseline SAIGE model.

Background: Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for "Post COVID-19 condition, unspecified" to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear., Objective: This study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems-the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center-against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions., Methods: Patients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19-related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a "core" cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code's performance was compared across 3 health care systems and across different time periods of the pandemic., Results: Overall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems., Conclusions: This is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code., (©Monika Maripuri, Andrew Dey, Jacqueline Honerlaw, Chuan Hong, Yuk-Lam Ho, Vidisha Tanukonda, Alicia W Chen, Vidul Ayakulangara Panickan, Xuan Wang, Harrison G Zhang, Doris Yang, Malarkodi Jebathilagam Samayamuthu, Michele Morris, Shyam Visweswaran, Brendin Beaulieu-Jones, Rachel Ramoni, Sumitra Muralidhar, J Michael Gaziano, Katherine Liao, Zongqi Xia, Gabriel A Brat, Tianxi Cai, Kelly Cho. Originally published in the Online Journal of Public Health Informatics (https://ojphi.jmir.org/), 03.05.2024.)

Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular etiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program followed by multi-ancestry meta-analysis with the previous largest FECD GWAS, for a total of 3970 cases and 333,794 controls. We confirm the previous four loci, and identify eight novel loci: SSBP3, THSD7A, LAMB1, PIDD1, RORA, HS3ST3B1, LAMA5, and COL18A1. We further confirm the TCF4 locus in GWAS for admixed African and Hispanic/Latino ancestries and show an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling, validated through homology, suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and colocalization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function., (© 2024. The Author(s).)

The Phenome-Wide Association Study (PheWAS) is increasingly used to broadly screen for potential treatment effects, e.g., IL6R variant as a proxy for IL6R antagonists. This approach offers an opportunity to address the limited power in clinical trials to study differential treatment effects across patient subgroups. However, limited methods exist to efficiently test for differences across subgroups in the thousands of multiple comparisons generated as part of a PheWAS. In this study, we developed an approach that maximizes the power to test for heterogeneous genotype-phenotype associations and applied this approach to an IL6R PheWAS among individuals of African (AFR) and European (EUR) ancestries. We identified 29 traits with differences in IL6R variant-phenotype associations, including a lower risk of type 2 diabetes in AFR (OR 0.96) vs EUR (OR 1.0, p-value for heterogeneity = 8.5 × 10 -3 ), and higher white blood cell count (p-value for heterogeneity = 8.5 × 10 -131 ). These data suggest a more salutary effect of IL6R blockade for T2D among individuals of AFR vs EUR ancestry and provide data to inform ongoing clinical trials targeting IL6 for an expanding number of conditions. Moreover, the method to test for heterogeneity of associations can be applied broadly to other large-scale genotype-phenotype screens in diverse populations., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)