Predicting oncology Drug-Induced cardiotoxicity with Donor-Specific iPSC-CMs-a proof-of-Concept study with doxorubicin.

Many oncology drugs have been found to induce cardiotoxicity in a subset of patients, which significantly limits their clinical use and impedes the benefit of lifesaving anti-cancer treatments. Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) carry donor-specific genetic information and have been proposed for exploring the inter-individual difference in oncology drug-induced cardiotoxicity. Herein, we evaluated the inter- and intra- individual variability of iPSC-CM-related assays and presented a proof of concept to prospectively predict doxorubicin (DOX)-induced cardiotoxicity (DIC) using donor-specific iPSC-CMs. Our findings demonstrated that donor-specific iPSC-CMs exhibited greater line-to-line variability than the intra-individual variability in impedance cytotoxicity and transcriptome assays. The variable and dose-dependent cytotoxic responses of iPSC-CMs resembled those observed in clinical practice, and largely replicated the reported mechanisms. By categorizing iPSC-CMs into resistant and sensitive cell lines based on their time- and concentration-related phenotypic responses to DOX, we found that the sensitivity of donor-specific iPSC-CMs to DOX may predict in vivo DIC risk. Furthermore, we identified a differentially expressed gene, DND microRNA-mediated repression inhibitor 1 (DND1), between the DOX-resistant and DOX-sensitive iPSC-CMs. Our results support the utilization of donor-specific iPSC-CMs in assessing inter-individual difference in DIC. Further studies will encompass a large panel of donor-specific iPSC-CMs to identify potential novel molecular and genetic biomarkers for predicting DOX and other oncology drug-induced cardiotoxicity.

Polygenic Risk for Type 2 Diabetes in African Americans.

African Americans (AAs) have been underrepresented in polygenic risk score (PRS) studies. Herein, we integrated genome-wide data from multiple observational studies on type 2 diabetes (T2D), encompassing a total of 101,987 AAs, to train and optimize an AA focused T2D PRS (PRSAA), using a Bayesian polygenic modeling method (PRS-CS). We further tested the score in three independent studies with a total of 7,275 AAs. We then compared the PRSAA to other published scores. Results show that a 1 standard deviation increase in the PRSAA was associated with 40%-60% increase in the odds of T2D (OR=1.60, 95% CI 1.37-1.88; OR=1.40, 95% CI 1.16-1.70; and OR=1.45, 95% CI 1.30-1.62) across three testing cohorts. These models captured 1.0%-2.6% of the variance (R2) in T2D on the liability scale. The positive predictive values (PPV) for three calculated score thresholds (the top 2%, 5% 10%) ranged from 14% to 35%. The PRSAA, in general, performed similarly to existing T2D PRS. Larger datasets remain needed to continue to evaluate the utility of within-ancestry scores in the AA population.

Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans.

BACKGROUND: African ancestry populations have the highest burden of stroke worldwide, yet the genetic basis of stroke in these populations is obscure. The Stroke Investigative Research and Educational Network (SIREN) is a multicenter study involving 16 sites in West Africa. We conducted the first-ever genome-wide association study (GWAS) of stroke in indigenous Africans. METHODS: Cases were consecutively recruited consenting adults (aged > 18 years) with neuroimaging-confirmed ischemic stroke. Stroke-free controls were ascertained using a locally validated Questionnaire for Verifying Stroke-Free Status. DNA genotyping with the H3Africa array was performed, and following initial quality control, GWAS datasets were imputed into the NIH Trans-Omics for Precision Medicine (TOPMed) release2 from BioData Catalyst. Furthermore, we performed fine-mapping, trans-ethnic meta-analysis, and in silico functional characterization to identify likely causal variants with a functional interpretation. RESULTS: We observed genome-wide significant (P-value < 5.0E-8) SNPs associations near AADACL2 and miRNA (MIR5186) genes in chromosome 3 after adjusting for hypertension, diabetes, dyslipidemia, and cardiac status in the base model as covariates. SNPs near the miRNA (MIR4458) gene in chromosome 5 were also associated with stroke (P-value < 1.0E-6). The putative genes near AADACL2, MIR5186, and MIR4458 genes were protective and novel. SNPs associations with stroke in chromosome 2 were more than 77 kb from the closest gene LINC01854 and SNPs in chromosome 7 were more than 116 kb to the closest gene LINC01446 (P-value < 1.0E-6). In addition, we observed SNPs in genes STXBP5-AS1 (chromosome 6), GALTN9 (chromosome 12), FANCA (chromosome 16), and DLGAP1 (chromosome 18) (P-value < 1.0E-6). Both genomic regions near genes AADACL2 and MIR4458 remained significant following fine mapping. CONCLUSIONS: Our findings identify potential roles of regulatory miRNA, intergenic non-coding DNA, and intronic non-coding RNA in the biology of ischemic stroke. These findings reveal new molecular targets that promise to help close the current gaps in accurate African ancestry-based genetic stroke's risk prediction and development of new targeted interventions to prevent or treat stroke.

Pharmacogenomics of Coronary Artery Response to Intravenous Gamma Globulin in Kawasaki Disease.

Background: Kawasaki disease (KD) is a multisystem inflammatory illness of infants and young children that can result in acute vasculitis. The pathological walls of afflicted coronary arteries show propensity for forming thrombosis and aneurysms. The mechanism of coronary artery aneurysms (CAA) despite intravenous gamma globulin (IVIG) treatment is not known. Methods: We performed a Whole Genome Sequencing (WGS) association analysis in a racially diverse cohort of KD patients treated with IVIG, both using AHA guidelines. We defined coronary aneurysm (CAA) (N = 234) as coronary z>2.5 and large coronary aneurysm (CAA/L) (N = 92) as z>5.0. We conducted logistic regression models to examine the association of genetic variants with CAA/L during acute KD and with persistence >6 weeks using an additive model between cases and 238 controls with no CAA. We adjusted for age, gender and three principal components of genetic ancestry. We performed functional mapping and annotation (FUMA) analysis and further assessed the predictive risk score of genomic risk loci using the area under the receiver operating characteristic curve (AUC). Results: The top significant variants associated with CAA/L were in the intergenic regions (rs62154092 p<6.32E-08 most significant). Variants in SMAT4, LOC100127 , PTPRD, TCAF2 and KLRC2 were the most significant non-intergenic SNPs. FUMA identified 12 genomic risk loci with eQTL or chromatin interactions mapped to 48 genes. Of these NDUFA5 has been implicated in KD CAA and MICU and ZMAT4 has potential functional implications. Genetic risk score using these 12 genomic risk loci yielded an AUC of 0.86. Conclusions: This pharmacogenomics study provides insights into the pathogenesis of CAA/L in IVIG-treated KD patients. We have identified multiple novel SNPs associated with CAA/L and related genes with potential functional implications. The study shows that genomics can help define the cause of CAA/L to guide management and improve risk stratification of KD patients.

The Pace of Biological Aging Predicts Nonspecific Chronic Low Back Pain Severity.

This study aimed to determine if and how the pace of biological aging was associated with nonspecific chronic low back pain (cLBP) and compare what measure of epigenetic age acceleration most strongly predicts cLBP outcomes. We used the Dunedin Pace of Aging from the Epigenome (DunedinPACE), Horvath's, Hannum's, and PhenoAge clocks to determine the pace of biological aging in 69 cLBP, and 49 pain-free controls (PFCs) adults, ages 18 to 85 years. On average, participants with cLBP had higher DunedinPACE (P < .001) but lower Horvath (P = .04) and Hannum (P = .02) accelerated epigenetic age than PFCs. There was no significant difference in PhenoAge acceleration between the cLBP and PFC groups (P = .97). DunedinPACE had the largest effect size (Cohen's d = .78) on group differences. In univariate regressions, a unit increase in DunedinPACE score was associated with 265.98 times higher odds of cLBP than the PFC group (P < .001). After controlling for sex, race, and body mass index (BMI), the odds ratio of cLBP to PFC group was 149.62 (P < .001). Furthermore, among participants with cLBP, DunedinPACE scores positively correlated with pain severity (rs = .385, P = .001) and interference (rs = .338, P = .005). Epigenetic age acceleration from Horvath, Hannum, and PhenoAge clocks were not significant predictors of cLBP. The odds of a faster pace of biological aging are higher among adults with cLBP, and this was associated with greater pain severity and disability. Future interventions to slow the pace of biological aging may improve cLBP outcomes. PERSPECTIVES: Accelerated epigenetic aging is common among adults with nonspecific cLBP. Higher DunedinPACE scores positively correlate with pain severity and interference, and better predict cLBP than other DNA methylation clocks. Interventions to slow the pace of biological aging may be viable targets for improving pain outcomes.

The pace of biological aging helps explain the association between insomnia and chronic low back pain.

Chronic low back pain (cLBP) is associated with insomnia and advanced age. Emerging evidence suggests that the severity of both sleep disorders (like insomnia) and chronic pain are associated with a faster pace of biological aging. We aimed to determine whether the pace of biological age mediates the relationship between insomnia and the impact of cLBP in a sample of community-dwelling adults ages 19 to 85 years. Participants (49 with no pain, 32 with low-impact pain, and 37 with high-impact pain) completed sociodemographic, pain, insomnia, and short physical performance battery assessments. We calculated the pace of biological aging using DunedinPACE from blood leukocyte DNA. On average, individuals with high-impact cLBP had significantly faster biological aging than those with low-impact and no chronic pain (p < .001). Bivariate associations of DunedinPACE scores with insomnia severity and functional performance were significant at p < .01 (rs = 0.324 and -0.502, respectively). After adjusting for race and sex, the association of insomnia severity and the impact of cLBP was partially mediated by the pace of biological aging (ß = 0.070, p < .001). Also, the association of insomnia severity with functional performance was partially mediated by the pace of biological aging (ß = -0.105, p < .001). Thus, insomnia remains strongly predictive of cLBP outcomes, and the pace of biological aging helps explain this association. Future prospective studies with repeated assessments are needed to uncover the directionality of these complex relationships and ultimately develop interventions to manage cLBP.

Metabolite profiles and DNA methylation in metabolic syndrome: a two-sample, bidirectional Mendelian randomization.

Introduction: Metabolic syndrome (MetS) increases the risk of cardiovascular disease and death. Previous '-omics' studies have identified dysregulated serum metabolites and aberrant DNA methylation in the setting of MetS. However, the relationship between the metabolome and epigenome have not been elucidated. In this study, we identified serum metabolites associated with MetS and DNA methylation, and we conducted bidirectional Mendelian randomization (MR) to assess causal relationships between metabolites and methylation. Methods: We leveraged metabolomic and genomic data from a national United States cohort of older adults (REGARDS), as well as metabolomic, epigenomic, and genomic data from a family-based study of hypertension (HyperGEN). We conducted metabolite profiling for MetS in REGARDS using weighted logistic regression models and validated them in HyperGEN. Validated metabolites were selected for methylation studies which fit linear mixed models between metabolites and six CpG sites previously linked to MetS. Statistically significant metabolite-CpG pairs were selected for two-sample, bidirectional MR. Results: Forward MR indicated that glucose and serine metabolites were causal on CpG methylation near CPT1A [B(SE): -0.003 (0.002), p = 0.028 and B(SE): 0.029 (0.011), p = 0.030, respectively] and that serine metabolites were causal on ABCG1 [B(SE): -0.008(0.003), p = 0.006] and SREBF1 [B(SE): -0.009(0.004), p = 0.018] methylation, which suggested a protective effect of serine. Reverse MR showed a bidirectional relationship between cg06500161 (ABCG1) and serine [B(SE): -1.534 (0.668), p = 0.023]. Discussion: The metabolome may contribute to the relationship between MetS and epigenetic modifications.

Identification of Trichomonas vaginalis 5-Nitroimidazole Resistance Targets.

Trichomonas vaginalis is the most common non-viral sexually transmitted infection. 5-nitroimidazoles are the only FDA-approved medications for T. vaginalis treatment. However, 5-nitroimidazole resistance has been increasingly recognized and may occur in up to 10% of infections. We aimed to delineate mechanisms of T. vaginalis resistance using transcriptome profiling of metronidazole (MTZ)-resistant and sensitive T. vaginalis clinical isolates. In vitro, 5-nitroimidazole susceptibility testing was performed to determine minimum lethal concentrations (MLCs) for T. vaginalis isolates obtained from women who had failed treatment (n = 4) or were successfully cured (n = 4). RNA sequencing, bioinformatics, and biostatistical analyses were performed to identify differentially expressed genes (DEGs) in the MTZ-resistant vs. sensitive T. vaginalis isolates. RNA sequencing identified 304 DEGs, 134 upregulated genes and 170 downregulated genes in the resistant isolates. Future studies with more T. vaginalis isolates with a broad range of MLCs are needed to determine which genes may represent the best alternative targets in drug-resistant strains.

Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program.

Introduction: Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive (AHT) classes to achieve blood pressure (BP) control. In the current study, we conducted single-variant and gene-based analyses of aTRH among individuals from 12 Trans-Omics for Precision Medicine cohorts with whole-genome sequencing data. Methods: Cases were defined as individuals treated for hypertension (HTN) taking three different AHT classes, with average systolic BP ≥ 140 or diastolic BP ≥ 90 mmHg, or four or more medications regardless of BP (n = 1,705). A normotensive control group was defined as individuals with BP < 140/90 mmHg (n = 22,079), not on AHT medication. A second control group comprised individuals who were treatment responsive on one AHT medication with BP < 140/ 90 mmHg (n = 5,424). Logistic regression with kinship adjustment using the Scalable and Accurate Implementation of Generalized mixed models (SAIGE) was performed, adjusting for age, sex, and genetic ancestry. We assessed variants using SKAT-O in rare-variant analyses. Single-variant and gene-based tests were conducted in a pooled multi-ethnicity stratum, as well as self-reported ethnic/racial strata (European and African American). Results: One variant in the known HTN locus, KCNK3, was a top finding in the multi-ethnic analysis (p = 8.23E-07) for the normotensive control group [rs12476527, odds ratio (95% confidence interval) = 0.80 (0.74-0.88)]. This variant was replicated in the Vanderbilt University Medical Center's DNA repository data. Aggregate gene-based signals included the genes AGTPBP, MYL4, PDCD4, BBS9, ERG, and IER3. Discussion: Additional work validating these loci in larger, more diverse populations, is warranted to determine whether these regions influence the pathobiology of aTRH.

Pharmacogenomics of intravenous immunoglobulin response in Kawasaki disease.

Introduction: Kawasaki disease (KD) is a diffuse vasculitis in children. Response to high dose intravenous gamma globulin (IVIG), the primary treatment, varies according to genetic background. We sought to identify genetic loci, which associate with treatment response using whole genome sequencing (WGS). Method: We performed WGS in 472 KD patients with 305 IVIG responders and 167 non-responders defined by AHA clinical criteria. We conducted logistic regression models to test additive genetic effect in the entire cohort and in four subgroups defined by ancestry information markers (Whites, African Americans, Asians, and Hispanics). We performed functional mapping and annotation using FUMA to examine genetic variants that are potentially involved IVIG non-response. Further, we conducted SNP-set [Sequence] Kernel Association Test (SKAT) for all rare and common variants. Results: Of the 43,288,336 SNPs (23,660,970 in intergenic regions, 16,764,594 in introns and 556,814 in the exons) identified, the top ten hits associated with IVIG non-response were in FANK1, MAP2K3:KCNJ12, CA10, FRG1DP, CWH43 regions. When analyzed separately in ancestry-based racial subgroups, SNPs in several novel genes were associated. A total of 23 possible causal genes were pinpointed by positional and chromatin mapping. SKAT analysis demonstrated association in the entire MANIA2, EDN1, SFMBT2, and PPP2R5E genes and segments of CSMD2, LINC01317, HIVEPI, HSP90AB1, and TTLL11 genes. Conclusions: This WGS study identified multiple predominantly novel understudied genes associated with IVIG response. These data can serve to inform regarding pathogenesis of KD, as well as lay ground work for developing treatment response predictors.

Novel genetic loci associated with osteoarthritis in multi-ancestry analyses in the Million Veteran Program and UK Biobank.

Osteoarthritis is a common progressive joint disease. As no effective medical interventions are available, osteoarthritis often progresses to the end stage, in which only surgical options such as total joint replacement are available. A more thorough understanding of genetic influences of osteoarthritis is essential to develop targeted personalized approaches to treatment, ideally long before the end stage is reached. To date, there have been no large multiancestry genetic studies of osteoarthritis. Here, we leveraged the unique resources of 484,374 participants in the Million Veteran Program and UK Biobank to address this gap. Analyses included participants of European, African, Asian and Hispanic descent. We discovered osteoarthritis-associated genetic variation at 10 loci and replicated findings from previous osteoarthritis studies. We also present evidence that some osteoarthritis-associated regions are robust to population ancestry. Drug repurposing analyses revealed enrichment of targets of several medication classes and provide potential insight into the etiology of beneficial effects of antiepileptics on osteoarthritis pain.

Stroke genetics informs drug discovery and risk prediction across ancestries.

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

Genetic Contributors of Efficacy and Adverse Metabolic Effects of Chlorthalidone in African Americans from the Genetics of Hypertension Associated Treatments (GenHAT) Study.

Hypertension is a leading risk factor for cardiovascular disease mortality. African Americans (AAs) have the highest prevalence of hypertension in the United States, and to alleviate the burden of hypertension in this population, better control of blood pressure (BP) is needed. Previous studies have shown considerable interpersonal differences in BP response to antihypertensive treatment, suggesting a genetic component. Utilizing data from 4297 AA participants randomized to chlorthalidone from the Genetics of Hypertension Associated Treatments (GenHAT) study, we aimed to identify variants associated with the efficacy of chlorthalidone. An additional aim was to find variants that contributed to changes in fasting glucose (FG) in these individuals. We performed genome-wide association analyses on the change of systolic and diastolic BP (SBP and DBP) over six months and FG levels over 24 months of treatment. We sought replication in the International Consortia of Pharmacogenomics Studies. We identified eight variants statistically associated with BP response and nine variants associated with FG response. One suggestive LINC02211-CDH9 intergenic variant was marginally replicated with the same direction of effect. Given the impact of hypertension in AAs, this study implies that understanding the genetic background for BP control and glucose changes during chlorthalidone treatment may help prevent adverse cardiovascular events in this population.

Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations.

BACKGROUND: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. METHODS: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. RESULTS: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. CONCLUSIONS: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Genome-wide polygenic score to predict chronic kidney disease across ancestries.

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension.

BACKGROUND: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. METHODS: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. RESULTS: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P<5×10-8). Among them, a rare intergenic variant at novel locus, LOC100506274, was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; P=4.99×10-8) but not stage-2 analysis (P=0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; P=4.18×10-7) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; P=7.28×10-23). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (P<1×10-6 and P<1×10-4, respectively). DISCUSSION: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

An Amish founder population reveals rare-population genetic determinants of the human lipidome.

Identifying the genetic determinants of inter-individual variation in lipid species (lipidome) may provide deeper understanding and additional insight into the mechanistic effect of complex lipidomic pathways in CVD risk and progression beyond simple traditional lipids. Previous studies have been largely population based and thus only powered to discover associations with common genetic variants. Founder populations represent a powerful resource to accelerate discovery of previously unknown biology associated with rare population alleles that have risen to higher frequency due to genetic drift. We performed a genome-wide association scan of 355 lipid species in 650 individuals from the Amish founder population including 127 lipid species not previously tested. To the best of our knowledge, we report for the first time the lipid species associated with two rare-population but Amish-enriched lipid variants: APOB_rs5742904 and APOC3_rs76353203. We also identified novel associations for 3 rare-population Amish-enriched loci with several sphingolipids and with proposed potential functional/causal variant in each locus including GLTPD2_rs536055318, CERS5_rs771033566, and AKNA_rs531892793. We replicated 7 previously known common loci including novel associations with two sterols: androstenediol with UGT locus and estriol with SLC22A8/A24 locus. Our results show the double power of founder populations and detailed lipidome to discover novel trait-associated variants.

Maternal soybean genistein on prevention of later-life breast cancer through inherited epigenetic regulations.

Breast cancer has strong developmental origins and maternal nutrition composition may influence later-life breast cancer risk in the offspring. Our study focused on a bioactive dietary component, genistein (GE) enriched in soybean products, to investigate specific timing of maternal GE exposure that may influence preventive efficacy of GE on offspring breast cancer later in life, and to explore the potential epigenetic mechanisms. Our results indicate a time-dependent effect of maternal GE exposure on early-life breast cancer development in offspring mice. Through integrated transcriptome and methylome analyses, we identified several candidate genes showing significantly differential gene expression and DNA methylation changes. We further found maternal long-term GE treatment can induce inherited epigenetic landmark changes in a candidate tumor suppressor gene, Trp63, resulting in transcriptional activation of Trp63 and induction of the downstream target genes. Our results suggest that maternal long-term exposure to soybean GE may influence early-life epigenetic reprogramming processes, which may contribute to its temporal preventive effects on breast cancer in the offspring. This study provides important mechanistic insights into an appropriate maternal administration of soybean products on prevention of breast cancer later in offspring life.

Genomic alterations associated with mutational signatures, DNA damage repair and chromatin remodeling pathways in cervical carcinoma.

Despite recent advances in the prevention of cervical cancer, the disease remains a leading cause of cancer-related deaths in women worldwide. By applying the GISTIC2.0 and/or the MutSig2CV algorithms on 430 whole-exome-sequenced cervical carcinomas, we identified previously unreported significantly mutated genes (SMGs) (including MSN, GPX1, SPRED3, FAS, and KRT8), amplifications (including NFIA, GNL1, TGIF1, and WDR87) and deletions (including MIR562, PVRL1, and NTM). Subset analyses of 327 squamous cell carcinomas and 86 non-squamous cell carcinomas revealed previously unreported SMGs in BAP1 and IL28A, respectively. Distinctive copy number alterations related to tumors predominantly enriched for *CpG- and Tp*C mutations were observed. CD274, GRB2, KRAS, and EGFR were uniquely significantly amplified within the Tp*C-enriched tumors. A high frequency of aberrations within DNA damage repair and chromatin remodeling genes were detected. Facilitated by the large sample size derived from combining multiple datasets, this study reveals potential targets and prognostic markers for cervical cancer.