Genome-wide studies in pharmacogenomics: harnessing the power of extreme phenotypes

Uncovering Predictors of Lipid Goal Attainment in Type 2 Diabetes Outpatients Using Logic Learning Machine: Insights from the AMD Annals and AMD Artificial Intelligence Study Group

Identifying and treating lipid abnormalities is crucial for preventing cardiovascular disease in diabetic patients, yet only two-thirds of patients reach recommended cholesterol levels. Elucidating the factors associated with lipid goal attainment represents an unmet clinical need. To address this knowledge gap, we conducted a real-world analysis of the lipid profiles of 11.252 patients from the Annals of the Italian Association of Medical Diabetologists (AMD) database from 2005 to 2019. We used a Logic Learning Machine (LLM) to extract and classify the most relevant variables predicting the achievement of a low-density lipoprotein cholesterol (LDL-C) value lower than 100 mg/dL (2.60 mmol/L) within two years of the start of lipid-lowering therapy. Our analysis showed that 61.4% of the patients achieved the treatment goal. The LLM model demonstrated good predictive performance, with a precision of 0.78, accuracy of 0.69, recall of 0.70, F1 Score of 0.74, and ROC-AUC of 0.79. The most significant predictors of achieving the treatment goal were LDL-C values at the start of lipid-lowering therapy and their reduction after six months. Other predictors of a greater likelihood of reaching the target included high-density lipoprotein cholesterol, albuminuria, and body mass index at baseline, as well as younger age, male sex, more follow-up visits, no therapy discontinuation, higher Q-score, lower blood glucose and HbA1c levels, and the use of anti-hypertensive medication. At baseline, for each LDL-C range analysed, the LLM model also provided the minimum reduction that needs to be achieved by the next six-month visit to increase the likelihood of reaching the therapeutic goal within two years. These findings could serve as a useful tool to inform therapeutic decisions and to encourage further in-depth analysis and testing.

Genomic architecture of phenotypic extremes in a wild cervid

Identifying the genes underlying fitness-related traits such as body size and male ornamentation can provide tools for conservation and management and are often subject to various selective pressures. Here we performed high-depth whole genome re-sequencing of pools of individuals representing the phenotypic extremes for antler and body size in white-tailed deer (Odocoileus virginianus). Samples were selected from a tissue repository containing phenotypic data for 4,466 male white-tailed deer from Anticosti Island, Quebec, with four pools representing the extreme phenotypes for antler and body size after controlling for age. Our results revealed a largely homogenous population but detected highly divergent windows between pools for both traits, with the mean allele frequency difference of 14% for and 13% for antler and body SNPs in outlier windows, respectively. Genes in outlier antler windows were enriched for pathways associated with cell death and protein metabolism and some of the most differentiated windows included genes associated with oncogenic pathways and reproduction, processes consistent with antler evolution and growth. Genes associated with body size were more nuanced, suggestive of a highly complex trait. Overall, this study revealed the complex genomic make-up of both antler morphology and body size in free-ranging white-tailed deer and identified target loci for additional analyses.

Regulatory CDH4 Genetic Variants Associate With Risk to Develop Capecitabine-Induced Hand-Foot Syndrome

Capecitabine-induced hand-foot syndrome (CiHFS) is a common dermatological adverse reaction affecting around 30% of patients with capecitabine-treated cancer, and the main cause of dose reductions and chemotherapy delays. To identify novel genetic factors associated with CiHFS in patients with cancer, we carried out an extreme-phenotype genomewide association study in 166 patients with breast and colorectal capecitabine-treated cancer with replication in a second cohort of 85 patients. We discovered and replicated a cluster of four highly correlated single-nucleotide polymorphisms associated with susceptibility to CiHFS at 20q13.33 locus (top hit = rs6129058, hazard ratio = 2.40, 95% confidence interval = 1.78-3.20; P = 1.2 × 10^-8 ). Using circular chromosome conformation capture sequencing, we identified a chromatin contact between the locus containing the risk alleles and the promoter of CDH4, located 90 kilobases away. The risk haplotype was associated with decreased levels of CDH4 mRNA and the protein it encodes, R-cadherin (RCAD), which mainly localizes in the granular layer of the epidermis. In human keratinocytes, CDH4 downregulation resulted in reduced expression of involucrin, a protein of the cornified envelope, an essential structure for skin barrier function. Immunohistochemical analyses revealed that skin from patients with severe CiHFS exhibited low levels of RCAD and involucrin before capecitabine treatment. Our results uncover a novel mechanism underlying individual genetic susceptibility to CiHFS with implications for clinically relevant risk prediction.

Effect of Genotype and Sex of the Host on the Bioavailability of Novel Albendazole Microcrystals Based on Chitosan and Cellulose Derivatives

Albendazole (ABZ), an anthelmintic compound widely used in the treatment of systemic nematode infections, is included in the list of class II drugs based on the Biopharmaceutical Classification System. ABZ has limited effectiveness due to its poor water solubility and consequent low bioavailability. Bioavailability of novel ABZ microcrystals based on hydroxyethylcellulose (S4A) or chitosan (S10A) was studied in male and female mice of two inbred lines, from the murine CBi-IGE model of trichinellosis, differing in susceptibility to this parasitosis (line CBi/L, resistant; line CBi+, susceptible). ABZ microcrystals were administered orally, and albendazole sulfoxide (ABZSO) was quantified in plasma by high-performance liquid chromatography. Mice given the microcrystals showed a significant increase in maximum plasmatic concentration (C_max) compared with those receiving pure ABZ (P < 0.01). In both genotypes, males and females given S4A had higher C_max than those receiving S10A (P < 0.05). CBi/L showed a greater C_max than CBi+ (significantly different only in females treated with S4A (P = 0.001)). CBi/L females attained a higher C_max than males (P < 0.05). No sex effect was observed for this variable in CBi+ (P > 0.05). The results of the pharmacokinetic analysis indicate that the microcrystalline formulations optimize ABZ bioavailability, both in males and females, S4A being the best system in CBi/L mice and S10A in CBi+. In summary, the microcrystals increased ABZ bioavailability, and under the conditions of this investigation, both host genotype and sex influenced the pharmacokinetic parameters measured.

RNA sequencing of bipolar disorder lymphoblastoid cell lines implicates the neurotrophic factor HRP-3 in lithium's clinical efficacy

Objectives: Lithium remains the oldest and most effective treatment for mood stabilisation in bipolar disorder (BD), even though at least half of patients are only partially responsive or do not respond. This study aimed to identify biomarkers associated with lithium response in BD, based on comparing RNA sequencing information derived from lymphoblastoid cell lines (LCLs) of lithium-responsive (LR) versus lithium non-responsive (LNR) BD patients, to assess gene expression variations that might bear on treatment outcome. Methods: RNA sequencing was carried out on 24 LCLs from female BD patients (12 LR and 12 LNR) followed by qPCR validation in two additional independent cohorts (41 and 17 BD patients, respectively). Results: Fifty-six genes showed nominal differential expression comparing LR and LNR (FC ≥ |1.3|, P ≤ 0.01). The differential expression of HDGFRP3 and ID2 was validated by qPCR in the independent cohorts. Conclusions: We observed higher expression levels of HDGFRP3 and ID2 in BD patients who favourably respond to lithium. Both of these genes are involved in neurogenesis, and HDGFRP3 has been suggested to be a neurotrophic factor. Additional studies in larger BD cohorts are needed to confirm the potential of HDGFRP3 and ID2 expression levels in blood cells as tentative favourable lithium response biomarkers.

Warfarin Anticoagulation Therapy in Caribbean Hispanics of Puerto Rico: A Candidate Gene Association Study

Existing algorithms account for ~50% of observed variance in warfarin dose requirements after including common polymorphisms. However, they do not perform as well in populations other than Caucasians, in part because some ethno-specific genetic variants are overlooked. The objective of the present study was to identify genetic polymorphisms that can explain variability in warfarin dose requirements among Caribbean Hispanics of Puerto Rico. Next-Generation Sequencing of candidate genes CYP2C9 and VKORC1 and genotyping by DMET® Plus Assay of cardiovascular patients were performed. We also aimed at characterizing the genomic structure and admixture pattern of this study cohort. Our study used the Extreme Discordant Phenotype approach to perform a case-control association analysis. The CYP2C9 variant rs2860905, which was found in all the major haplotypes occurring in the Puerto Rican population, showed stronger association with warfarin sensitivity (<4 mg/day) than common variants CYP2C9*2 and CYP2C9*3. Although, CYP2C9*2 and CYP2C9*3 are separately contained within two of the haplotypes, 10 subjects with the sensitive phenotype were carriers of only the CYP2C9 rs2860905 variant. Other polymorphisms in CES2 and ABCB1 were found to be associated with warfarin resistance. Incorporation of rs2860905 in a regression model (R2 = 0.63, MSE = 0.37) that also includes additional genetics (i.e., VKORC1-1639 G>A; CYP2C9 rs1856908; ABCB1 c.IVS9-44A>G/ rs10276036; CES2 c.269-965A>G/ rs4783745) and non-genetic factors (i.e., hypertension, diabetes and age) showed better prediction of warfarin dose requirements than CYP2C9*2 and CYP2C9*3 combined (partial R2 = 0.132 vs. 0.023 and 0.007, respectively, p < 0.001). The genetic background of Puerto Ricans in the study cohort showed a tri-hybrid admixture pattern, with a slightly higher than expected contribution of Native American ancestry (25%). The genomic diversity of Puerto Ricans is highlighted by the presence of four different major haplotype blocks in the CYP2C9 locus. Although, our findings need further replication, this study contributes to the field by identifying novel genetic variants that increase predictability of stable warfarin dosing among Caribbean Hispanics.

Non-response to (statin) therapy: the importance of distinguishing non-responders from non-adherers in pharmacogenetic studies

PURPOSE

In pharmacogenetic research, genetic variation in non-responders and high responders is compared with the aim to identify the genetic loci responsible for this variation in response. However, an important question is whether the non-responders are truly biologically non-responsive or actually non-adherent? Therefore, the aim of this study was to describe, within the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER), characteristics of both non-responders and high responders of statin treatment in order to possibly discriminate non-responders from non-adherers.

METHODS

Baseline characteristics of non-responders to statin therapy (≤10 % LDL-C reduction) were compared with those of high responders (>40 % LDL-C reduction) through a linear regression analysis. In addition, pharmacogenetic candidate gene analysis was performed to show the effect of excluding non-responders from the analysis.

RESULTS

Non-responders to statin therapy were younger (p = 0.001), more often smoked (p < 0.001), had a higher alcohol consumption (p < 0.001), had lower LDL cholesterol levels (p < 0.001), had a lower prevalence of hypertension (p < 0.001), and had lower cognitive function (p = 0.035) compared to subjects who highly responded to pravastatin treatment. Moreover, excluding non-responders from pharmacogenetic studies yielded more robust results, as standard errors decreased.

CONCLUSION

Our results suggest that non-responders to statin therapy are more likely to actually be non-adherers, since they have more characteristics that are viewed as indicators of high self-perceived health and low disease awareness, possibly making the subjects less adherent to study medication. We suggest that in pharmacogenetic research, extreme non-responders should be excluded to overcome the problem that non-adherence is investigated instead of non-responsiveness.

Genetic data: The new challenge of personalized medicine, insights for rheumatoid arthritis patients

Rapid advances in genotyping technology, analytical methods, and the establishment of large cohorts for population genetic studies have resulted in a large new body of information about the genetic basis of human rheumatoid arthritis (RA). Improved understanding of the root pathogenesis of the disease holds the promise of improved diagnostic and prognostic tools based upon this information. In this review, we summarize the nature of new genetic findings in human RA, including susceptibility loci and gene-gene and gene-environment interactions, as well as genetic loci associated with sub-groups of patients and those associated with response to therapy. Possible uses of these data are discussed, such as prediction of disease risk as well as personalized therapy and prediction of therapeutic response and risk of adverse events. While these applications are largely not refined to the point of clinical utility in RA, it seems likely that multi-parameter datasets including genetic, clinical, and biomarker data will be employed in the future care of RA patients.

Whole-genome resequencing of extreme phenotypes in collared flycatchers highlights the difficulty of detecting quantitative trait loci in natural populations

Dissecting the genetic basis of phenotypic variation in natural populations is a long-standing goal in evolutionary biology. One open question is whether quantitative traits are determined only by large numbers of genes with small effects, or whether variation also exists in large-effect loci. We conducted genomewide association analyses of forehead patch size (a sexually selected trait) on 81 whole-genome-resequenced male collared flycatchers with extreme phenotypes, and on 415 males sampled independent of patch size and genotyped with a 50K SNP chip. No SNPs were genomewide statistically significantly associated with patch size. Simulation-based power analyses suggest that the power to detect large-effect loci responsible for 10% of phenotypic variance was <0.5 in the genome resequencing analysis, and <0.1 in the SNP chip analysis. Reducing the recombination by two-thirds relative to collared flycatchers modestly increased power. Tripling sample size increased power to >0.8 for resequencing of extreme phenotypes (N = 243), but power remained <0.2 for the 50K SNP chip analysis (N = 1245). At least 1 million SNPs were necessary to achieve power >0.8 when analysing 415 randomly sampled phenotypes. However, power of the 50K SNP chip to detect large-effect loci was nearly 0.8 in simulations with a small effective population size of 1500. These results suggest that reliably detecting large-effect trait loci in large natural populations will often require thousands of individuals and near complete sampling of the genome. Encouragingly, far fewer individuals and loci will often be sufficient to reliably detect large-effect loci in small populations with widespread strong linkage disequilibrium.

Genome-wide association study of warfarin maintenance dose in a Brazilian sample

AIM

Extreme discordant phenotype and genome-wide association (GWA) approaches were combined to explore the role of genetic variants on warfarin dose requirement in Brazilians.

METHODS

Patients receiving low (≤ 20 mg/week; n = 180) or high stable warfarin doses (≥ 42.5 mg/week; n = 187) were genotyped with Affymetrix Axiom(®) Biobank arrays. Imputation was carried out using data from the combined 1000 Genomes project.

RESULTS

Genome-wide signals (p ≤ 5 × 10(-8)) were identified in the well-known VKORC1 (lead SNP, rs749671; OR: 20.4; p = 1.08 × 10(-33)) and CYP2C9 (lead SNP, rs9332238, OR: 6.8 and p = 4.4 × 10(-13)) regions. The rs9332238 polymorphism is in virtually perfect LD with CYP2C9*2 (rs1799853) and CYP2C9*3 (rs1057910). No other genome-wide significant regions were identified in the study.

CONCLUSION

We confirmed the important role of VKORC1 and CYP2C9 polymorphisms in warfarin dose. Original submitted 14 January 2015; Revision submitted 26 May 2015.

Molecular insight into thiopurine resistance: transcriptomic signature in lymphoblastoid cell lines

Background

There has been considerable progress in the management of acute lymphoblastic leukemia (ALL) but further improvement is needed to increase long-term survival. The thiopurine agent 6-mercaptopurine (6-MP) used for ALL maintenance therapy has a key influence on clinical outcomes and relapse prevention. Genetic inheritance in thiopurine metabolism plays a major role in interindividual clinical response variability to thiopurines; however, most cases of thiopurine resistance remain unexplained.

Methods

We used lymphoblastoid cell lines (LCLs) from healthy donors, selected for their extreme thiopurine susceptibility. Thiopurine metabolism was characterized by the determination of TPMT and HPRT activity. We performed genome-wide expression profiling in resistant and sensitive cell lines with the goal of elucidating the mechanisms of thiopurine resistance.

Results

We determined a higher TPMT activity (+44%; P = 0.024) in resistant compared to sensitive cell lines, although there was no difference in HPRT activity. We identified a 32-gene transcriptomic signature that predicts thiopurine resistance. This signature includes the GTPBP4 gene coding for a GTP-binding protein that interacts with p53. A comprehensive pathway analysis of the genes differentially expressed between resistant and sensitive cell lines indicated a role for cell cycle and DNA mismatch repair system in thiopurine resistance. It also revealed overexpression of the ATM/p53/p21 pathway, which is activated in response to DNA damage and induces cell cycle arrest in thiopurine resistant LCLs. Furthermore, overexpression of the p53 target gene TNFRSF10D or the negative cell cycle regulator CCNG2 induces cell cycle arrest and may also contribute to thiopurine resistance. ARHGDIA under-expression in resistant cell lines may constitute a novel molecular mechanism contributing to thiopurine resistance based on Rac1 inhibition induced apoptosis and in relation with thiopurine pharmacodynamics.

Conclusion

Our study provides new insights into the molecular mechanisms underlying thiopurine resistance and suggests a potential research focus for developing tailored medicine.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0150-6) contains supplementary material, which is available to authorized users.

Whole-exome sequencing reveals defective CYP3A4 variants predictive of paclitaxel dose-limiting neuropathy

PURPOSE

Paclitaxel, a widely used chemotherapeutic drug, can cause peripheral neuropathies leading to dose reductions and treatment suspensions and decreasing the quality of life of patients. It has been suggested that genetic variants altering paclitaxel pharmacokinetics increase neuropathy risk, but the major causes of interindividual differences in susceptibility to paclitaxel toxicity remain unexplained. We carried out a whole-exome sequencing (WES) study to identify genetic susceptibility variants associated with paclitaxel neuropathy.

EXPERIMENTAL DESIGN

Blood samples from 8 patients with severe paclitaxel-induced peripheral neuropathy were selected for WES. An independent cohort of 228 cancer patients with complete paclitaxel neuropathy data was used for variant screening by DHPLC and association analysis. HEK293 cells were used for heterologous expression and characterization of two novel CYP3A4 enzymes.

RESULTS

WES revealed 2 patients with rare CYP3A4 variants, a premature stop codon (CYP3A4*20 allele) and a novel missense variant (CYP3A4*25, p.P389S) causing reduced enzyme expression. Screening for CYP3A4 variants in the independent cohort revealed three additional CYP3A4*20 carriers, and two patients with missense variants exhibiting diminished enzyme activity (CYP3A4*8 and the novel CYP3A4*27 allele, p.L475V). Relative to CYP3A4 wild-type patients, those carrying CYP3A4 defective variants had more severe neuropathy (2- and 1.3-fold higher risk of neuropathy for loss-of-function and missense variants, respectively, P = 0.045) and higher probability of neuropathy-induced paclitaxel treatment modifications (7- and 3-fold higher risk for loss-of-function and missense variants, respectively, P = 5.9 × 10(-5)).

CONCLUSION

This is the first description of a genetic marker associated with paclitaxel treatment modifications caused by neuropathy. CYP3A4 defective variants may provide a basis for paclitaxel treatment individualization.

Deciphering next-generation pharmacogenomics: an information technology perspective

In the post-genomic era, the rapid evolution of high-throughput genotyping technologies and the increased pace of production of genetic research data are continually prompting the development of appropriate informatics tools, systems and databases as we attempt to cope with the flood of incoming genetic information. Alongside new technologies that serve to enhance data connectivity, emerging information systems should contribute to the creation of a powerful knowledge environment for genotype-to-phenotype information in the context of translational medicine. In the area of pharmacogenomics and personalized medicine, it has become evident that database applications providing important information on the occurrence and consequences of gene variants involved in pharmacokinetics, pharmacodynamics, drug efficacy and drug toxicity will become an integral tool for researchers and medical practitioners alike. At the same time, two fundamental issues are inextricably linked to current developments, namely data sharing and data protection. Here, we discuss high-throughput and next-generation sequencing technology and its impact on pharmacogenomics research. In addition, we present advances and challenges in the field of pharmacogenomics information systems which have in turn triggered the development of an integrated electronic 'pharmacogenomics assistant'. The system is designed to provide personalized drug recommendations based on linked genotype-to-phenotype pharmacogenomics data, as well as to support biomedical researchers in the identification of pharmacogenomics-related gene variants. The provisioned services are tuned in the framework of a single-access pharmacogenomics portal.

RNA-Seq using two populations reveals genes and alleles controlling wood traits and growth in Eucalyptus nitens

Eucalyptus nitens is a perennial forest tree species grown mainly for kraft pulp production in many parts of the world. Kraft pulp yield (KPY) is a key determinant of plantation profitability and increasing the KPY of trees grown in plantations is a major breeding objective. To speed up the breeding process, molecular markers that can predict KPY are desirable. To achieve this goal, we carried out RNA-Seq studies on trees at extremes of KPY in two different trials to identify genes and alleles whose expression correlated with KPY. KPY is positively correlated with growth measured as diameter at breast height (DBH) in both trials. In total, six RNA bulks from two treatments were sequenced on an Illumina HiSeq platform. At 5% false discovery rate level, 3953 transcripts showed differential expression in the same direction in both trials; 2551 (65%) were down-regulated and 1402 (35%) were up-regulated in low KPY samples. The genes up-regulated in low KPY trees were largely involved in biotic and abiotic stress response reflecting the low growth among low KPY trees. Genes down-regulated in low KPY trees mainly belonged to gene categories involved in wood formation and growth. Differential allelic expression was observed in 2103 SNPs (in 1068 genes) and of these 640 SNPs (30%) occurred in 313 unique genes that were also differentially expressed. These SNPs may represent the cis-acting regulatory variants that influence total gene expression. In addition we also identified 196 genes which had Ka/Ks ratios greater than 1.5, suggesting that these genes are under positive selection. Candidate genes and alleles identified in this study will provide a valuable resource for future association studies aimed at identifying molecular markers for KPY and growth.

Pharmacogenomics of osteoporotic fractures

Osteoporosis is a prevalent disease that typically reduces bone strength and predisposes to fractures. It is a multifactorial disorder resulting from the interaction of genetic and acquired factors. Candidate gene studies and, more recently, genome-wide studies have identified a number of polymorphisms significantly associated with bone mass and fractures. Anti-resorptive drugs, which inhibit the differentiation and activity of osteoclasts, are frequently used to treat patients with osteoporosis.Several candidate gene studies have explored the association of genetic factors with drug response, including some common polymorphisms of the gene encoding FDPS (Farnesyl diphosphate synthase), an enzyme that is the main target of aminobisphosphonates. Although scarce data are available, interesting opportunities are open for a better understanding of the pharmacogenetics of osteoporosis and osteoporotic fractures. They include the reanalysis of data already available from epidemiological studies and clinical trials, as well as obtaining pharmacogenetic data in new studies. However, based upon the experience with previous genome-wide association studies, large collaborative efforts would be likely needed to obtain meaningful results.