Citations

Introduction Despite the identification of multiple susceptibility loci by genome-wide association studies (GWAS), considerable chronic obstructive pulmonary disease (COPD) heritability remains unexplained. Aim To identify interaction networks of airway epithelial cell DNA methylation in COPD and further explore potential correlations with airway bacterial composition, as potentially collective regulators of biological pathways influencing COPD severity. Methods Using DNA isolated from bronchial airway brushings of 67 ever-smokers (>20 pack-years) from the SubPopulations and InteRmediate Outcomes Measures in COPD Study (SPIROMICS), we assessed proportion of DNA methylation (β) by epigenome-wide association study (EWAS) and examined associations of differentially methylated CpG probes (DMPs) with risk for moderate-to-severe COPD (N=34) versus absent or mild COPD (N=33). We tested co-methylation modules generated by Weighted Correlation Network Analyses (WGCNA) for associations with moderate-to-severe COPD and with bacterial genus-level relative abundances (16S rRNA sequencing). Results EWAS-identified nominally significant DMPs enriched for lung function GWAS loci. Eigengenes in six WGCNA modules were associated with moderate-to-severe COPD (false discovery rate <0.05). Four of those modules were enriched for forced expiratory volume in 1 s/forced vital capacity GWAS loci, and five overlapped with DMPs from EWAS. Overlapping CpG loci in three COPD-associated modules were adjacent to mucin genes; one had 10 genes highly ranked by connectivity with MUC5B, including important pathway genes: B3GNT6 , DGKI and ITGA8 . CpGs in an independent COPD-associated module showed the most correlations with Rothia , with directionality suggestive of negative associations with moderate-severe COPD. Conclusions Bronchial epithelial DNA methylation modules enriched for lung function GWAS loci associate with COPD severity in SPIROMICS. Potential module relationships to bronchial bacterial composition require further validation.

AbstractBackgroundAlzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non‐Hispanic White (NHW) population. To address this, Accelerating Medicines Partnership in AD (AMP‐AD) aimed to promote inclusivity in multi‐omics AD research, to unravel unique molecular signatures and pathways. The study aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial groups.MethodDorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (980 unique individuals), 322 were from African American donors, 214 from Latino Americans, 551 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG samples, 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag‐based mass spectrometry (TMT‐MS). Following quality control (QC), proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. Differential protein expression was conducted within and across races after adjusting for batch using regression‐analysis.ResultIn total, 9,180 proteins from the DLPFC, and 9,734 proteins from STG brain tissues were quantified by TMT‐MS. Further analysis identified approximately 3,000 differentially abundant proteins in AD brains compared to controls within race. The AD‐associated differentially abundant proteins were strongly correlated between DLPFC and STG regions and with CERAD and Braak. Protein levels of MAPT and APP demonstrated equivalent disease‐related elevations in both African American and NHW individuals with AD. Notably, after adjusting for AD, significant differences in protein levels were identified across race.ConclusionThe proteomics approach employed by AMP‐AD sheds light on the brain proteome in AD across diverse racial groups, emphasizing the importance of inclusive research in establishing robust and generalizable discoveries. The identified proteins here could underscore racial disparities beyond disease association, contributing to a more nuanced understanding of AD pathophysiology.

AbstractBackgroundAlzheimer’s disease (AD) is a devastating neurodegenerative disorder with few therapies to treat, mitigate or prevent its onset. Understanding of this disease is predominantly based on research in non‐Hispanic Whites (NHW) although AD disproportionately affects African Americans (AA) and Latin Americans (LA), underrepresented in AD research. To address this knowledge gap, the Accelerating Medicine Partnership for Alzheimer’s Disease (AMP‐AD) Diversity Working Group was launched to generate multi‐omics data from post‐mortem brain tissue from donors of predominantly AA and LA descent. Here, we focus on genomic and transcriptomics measures, made available through the AD Knowledge Portal (ADKP).MethodBrain tissue from dorsolateral prefrontal cortex (DLPFC), caudate nucleus (CN), superior temporal gyrus (STG) and temporal pole (TP) regions of AA (N = 299), LA (N = 344) and NHW (N = 532) donors was obtained through Mayo Clinic, Mt. Sinai School of Medicine, Emory, Columbia, Rush Alzheimer’s Disease Center, Banner Sun Health, and 1Florida. DNA extracted from DLPFC tissue samples (n = 641) was utilized for whole genome sequencing (WGS) at New York Genome Center (NYGC). RNAseq of 2,224 samples was conducted either at Mayo, Rush or NYGC. Sequencing reads were processed through GenomeGPS and MAPRseq pipelines for WGS and RNAseq data, respectively. Following quality control (QC), RNAseq data was normalized and assessed for sources of variation (SOV). Integration of WGS and RNAseq data to perform comparative eQTL analysis across multi‐ethnic populations and brain regions is ongoing.ResultWGS data for 621 donors, and RNAseq data generated at Mayo (n = 1,136 samples), Rush (n = 627), and NYGC (n = 779) sequencing centers, were deposited to the ADKP. Consensus processing of RNAseq data revealed site, sex, race/ethnicity, RIN, AD diagnosis, age at death and/or library batch as SOV across various sites and brain regions. Principal component analysis of gene expression measures revealed no major stratification by disease or brain region. Accompanying clinical metadata of donors have been distributed through ADKP.ConclusionThese multi‐omics data made available to the research community is expected to be an initial step towards bridging our data and knowledge gap to elucidate conserved and distinct AD related pathways across these underrepresented at‐risk populations.

Abstract INTRODUCTION Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within non‐Hispanic White (NHW) populations. Here we provide an extensive survey of the proteomic landscape of AD across diverse racial/ethnic groups. METHODS Two cortical regions, from multiple centers, were harmonized by uniform neuropathological diagnosis. Among 998 unique donors, 273 donors self‐identified as African American, 229 as Latino American, and 434 as NHW. RESULTS While amyloid precursor protein and the microtubule‐associated protein tau demonstrated higher abundance in AD brains, no significant race‐related differences were observed. Further proteome‐wide and focused analyses (specific amyloid beta [Aβ] species and the tau domains) supported the absence of racial differences in these AD pathologies within the brain proteome. DISCUSSION Our findings indicate that the racial differences in AD risk and clinical presentation are not underpinned by dramatically divergent patterns in the brain proteome, suggesting that other determinants account for these clinical disparities. Highlights We present a large‐scale proteome (∼10,000 proteins) of DLPFC (998) and STG (244) across AD cases. About 50% of samples were from racially and ethnically diverse brain donors. Key AD proteins (amyloid and tau) correlated with CERAD and Braak stages. No significant race‐related differences in amyloid and tau protein levels were observed in AD brains. AD‐associated protein changes showed a strong correlation between the brain proteomes of African American and White individuals. This dataset advances understanding of ethnoracial‐specific AD pathways and potential therapies.

Abstract INTRODUCTION Multi‐omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked Black Americans (BA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS To bridge this gap, Accelerating Medicines Partnership in Alzheimer's Disease (AMP‐AD) expanded brain multi‐omics profiling to multi‐ethnic donors. RESULTS We generated multi‐omics data and curated and harmonized phenotypic data from BA ( n = 306), LA ( n = 326), or BA and LA ( n = 4) brain donors plus non‐Hispanic White ( n = 252) and other ( n = 20) ethnic groups, to establish a foundational dataset enriched for BA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION The inclusion of traditionally underrepresented groups in multi‐omics studies is essential to discovering the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD. Highlights Accelerating Medicines Partnership in Alzheimer's Disease Diversity Initiative led brain tissue profiling in multi‐ethnic populations. Brain multi‐omics data is generated from Black American, Latin American, and non‐Hispanic White donors. RNA, whole genome sequencing and tandem mass tag proteomicsis completed and shared. Multiple brain regions including caudate, temporal and dorsolateral prefrontal cortex were profiled.

Abstract ZC3H18 is a multifunctional regulator of gene expression that is lost in a subset of high-grade serous ovarian cancers (HGSOC). Our prior studies have established that the loss of ZC3H18 diminishes BRCA1 levels, leading to the disruption of homologous recombination DNA repair (HR) and heightened sensitivity of HGSOC cells to PARP inhibitors. Here we show an additional facet to ZC3H18's impact, showing that its loss also induces a reprogramming of energy metabolism in HGSOC. Our findings demonstrate that the depletion of ZC3H18 results in reduced mRNA and protein levels of the NAD+-biosynthetic enzyme, NMNAT1, in HGSOC cells. Mechanistic studies uncovered that ZC3H18 occupies the NMNAT1 promoter, facilitating NMNAT1 transcription by recruiting CDK12 onto the promoter. Consistent with this mechanism, loss of ZC3H18 led to a reduction in CDK12 levels on the NMNAT1 promoter, diminishing NMNAT1 abundance and subsequently causing a decline in cellular NAD levels. These observations unveil a previously unknown role for ZC3H18 in HGSOC, shedding light on its involvement in the regulation of energy metabolism. Importantly, our findings provide valuable insights into potential therapeutic pathways that leverage the metabolic changes linked to ZC3H18 deficiency. Citation Format: Benjamin Wilson, Natalie Wilson, Xianfeng Chen, Shuwen Zhang, Chen Wang, Larry M. Karnitz, Scott H. Kaufmann, Arun Kanakkanthara. ZC3H18: A novel regulator of NAD+ metabolism in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4447.

Abstract Rationale In addition to rare genetic variants and the MUC5B locus, common genetic variants contribute to idiopathic pulmonary fibrosis (IPF) risk. The predictive power of common variants outside the MUC5B locus for IPF and interstitial lung abnormalities (ILAs) is unknown. Objectives We tested the predictive value of IPF polygenic risk scores (PRSs) with and without the MUC5B region on IPF, ILA, and ILA progression. Methods We developed PRSs that included (PRS-M5B) and excluded (PRS-NO-M5B) the MUC5B region (500-kb window around rs35705950-T) using an IPF genome-wide association study. We assessed PRS associations with area under the receiver operating characteristic curve (AUC) metrics for IPF, ILA, and ILA progression. Measurements and Main Results We included 14,650 participants (1,970 IPF; 1,068 ILA) from six multi-ancestry population-based and case–control cohorts. In cases excluded from genome-wide association study, the PRS-M5B (odds ratio [OR] per SD of the score, 3.1; P = 7.1 × 10−95) and PRS-NO-M5B (OR per SD, 2.8; P = 2.5 × 10−87) were associated with IPF. Participants in the top PRS-NO-M5B quintile had ∼sevenfold odds for IPF compared with those in the first quintile. A clinical model predicted IPF (AUC, 0.61); rs35705950-T and PRS-NO-M5B demonstrated higher AUCs (0.73 and 0.7, respectively), and adding both genetic predictors to a clinical model yielded the highest performance (AUC, 0.81). The PRS-NO-M5B was associated with ILA (OR, 1.25) and ILA progression (OR, 1.16) in European ancestry participants. Conclusions A common genetic variant risk score complements the MUC5B variant to identify individuals at high risk of interstitial lung abnormalities and pulmonary fibrosis.

Background: Clonal hematopoiesis (CH) of indeterminate potential (CHIP) is a risk factor for cardiovascular disease. The relationship between CHIP and coronary microvascular dysfunction (CMD) is unknown. The current study examines the association between CHIP and CH with CMD and the potential relationships in risk for adverse cardiovascular outcomes. Methods: In this retrospective observational study, targeted next-generation sequencing was performed for 177 participants with no coronary artery disease who presented with chest pain and underwent routine coronary functional angiogram. Patients with somatic mutations in leukemia-associated driver genes in hematopoietic stem and progenitor cells were examined; CHIP was considered at a variant allele fraction ≥2%; CH was considered at a variant allele fraction ≥1%. CMD was defined as coronary flow reserve to intracoronary adenosine of ≤2. Major adverse cardiovascular events considered were myocardial infarction, coronary revascularization, or stroke. Results: A total of 177 participants were examined. Mean follow-up was 12±7 years. A total of 17 patients had CHIP and 28 had CH. Cases with CMD (n=19) were compared with controls with no CMD (n=158). Cases were 56±9 years, were 68% women, and had more CHIP (27%; P =0.028) and CH (42%; P =0.001) than controls. CMD was associated with independent risk for major adverse cardiovascular events (hazard ratio, 3.89 [95% CI, 1.21–12.56]; P =0.023), and 32% of this risk was mediated by CH. The risk mediated by CH was ≈0.5× as large as the direct effect of CMD on major adverse cardiovascular events. Conclusions: In humans, we observe patients with CMD are more likely to have CHIP, and nearly one-third of major adverse cardiovascular events in CMD are mediated by CH.

AbstractIdentifying biomarkers associated with disease progression and drug resistance are important for personalized care. We investigated the expression of 121 curated genes, related to immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs) responsiveness. We analyzed 28 human multiple myeloma (MM) cell lines with known drug sensitivities and 130 primary MM patient samples collected at different disease stages, including newly diagnosed (ND), on therapy (OT), and relapsed and refractory (RR, collected within 12 months before the patients’ death) timepoints. Our findings led to the identification of a subset of genes linked to clinical drug resistance, poor survival, and disease progression following combination treatment containing IMIDs and/or PIs. Finally, we built a seven‐gene model (MM‐IMiD and PI sensitivity‐7 genes [IP‐7]) using digital gene expression profiling data that significantly separates ND patients from IMiD‐ and PI‐refractory RR patients. Using this model, we retrospectively analyzed RNA sequcencing (RNAseq) data from the Mulltiple Myeloma Research Foundation (MMRF) CoMMpass (n = 578) and Mayo Clinic MM patient registry (n = 487) to divide patients into probabilities of responder and nonresponder, which subsequently correlated with overall survival, disease stage, and number of prior treatments. Our findings suggest that this model may be useful in predicting acquired resistance to treatments containing IMiDs and/or PIs.