The power of genetic diversity in genome-wide association studies of lipids

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

PTEN and PI3K/AKT in non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer deaths worldwide. In the last years, the identification of activating EGFR mutations, conferring increased sensitivity and disease response to tyrosine kinase inhibitors, has changed the prospect of NSCLC patients. The PTEN/PI3K/AKT pathway regulates multiple cellular functions, including cell growth, differentiation, proliferation, survival, motility, invasion and intracellular trafficking. Alterations in this pathway, mainly PTEN inactivation, have been associated with resistance to EGFR-tyrosine kinase inhibitor therapy and lower survival in NSCLC patients. In this review, we will briefly discuss the main PTEN/PI3K/AKT pathway alterations found in NSCLC, as well as the cell processes regulated by PTEN/PI3K/AKT leading to tumorigenesis.

Genome-wide association meta-analysis for early age-related macular degeneration highlights novel loci and insights for advanced disease

BACKGROUND

Advanced age-related macular degeneration (AMD) is a leading cause of blindness. While around half of the genetic contribution to advanced AMD has been uncovered, little is known about the genetic architecture of early AMD.

METHODS

To identify genetic factors for early AMD, we conducted a genome-wide association study (GWAS) meta-analysis (14,034 cases, 91,214 controls, 11 sources of data including the International AMD Genomics Consortium, IAMDGC, and UK Biobank, UKBB). We ascertained early AMD via color fundus photographs by manual grading for 10 sources and via an automated machine learning approach for > 170,000 photographs from UKBB. We searched for early AMD loci via GWAS and via a candidate approach based on 14 previously suggested early AMD variants.

RESULTS

Altogether, we identified 10 independent loci with statistical significance for early AMD: (i) 8 from our GWAS with genome-wide significance (P < 5 × 10- 8), (ii) one previously suggested locus with experiment-wise significance (P < 0.05/14) in our non-overlapping data and with genome-wide significance when combining the reported and our non-overlapping data (together 17,539 cases, 105,395 controls), and (iii) one further previously suggested locus with experiment-wise significance in our non-overlapping data. Of these 10 identified loci, 8 were novel and 2 known for early AMD. Most of the 10 loci overlapped with known advanced AMD loci (near ARMS2/HTRA1, CFH, C2, C3, CETP, TNFRSF10A, VEGFA, APOE), except two that have not yet been identified with statistical significance for any AMD. Among the 17 genes within these two loci, in-silico functional annotation suggested CD46 and TYR as the most likely responsible genes. Presence or absence of an early AMD effect distinguished the known pathways of advanced AMD genetics (complement/lipid pathways versus extracellular matrix metabolism).

CONCLUSIONS

Our GWAS on early AMD identified novel loci, highlighted shared and distinct genetics between early and advanced AMD and provides insights into AMD etiology. Our data provide a resource comparable in size to the existing IAMDGC data on advanced AMD genetics enabling a joint view. The biological relevance of this joint view is underscored by the ability of early AMD effects to differentiate the major pathways for advanced AMD.

Genetic Susceptibility to Chronic Kidney Disease - Some More Pieces for the Heritability Puzzle

Chronic kidney disease (CKD) is a major global health problem with an increasing prevalence partly driven by aging population structure. Both genomic and environmental factors contribute to this complex heterogeneous disease. CKD heritability is estimated to be high (30-75%). Genome-wide association studies (GWAS) and GWAS meta-analyses have identified several genetic loci associated with CKD, including variants in UMOD, SHROOM3, solute carriers, and E3 ubiquitin ligases. However, these genetic markers do not account for all the susceptibility to CKD, and the causal pathways remain incompletely understood; other factors must be contributing to the missing heritability. Less investigated biological factors such as telomere length; mitochondrial proteins, encoded by nuclear genes or specific mitochondrial DNA (mtDNA) encoded genes; structural variants, such as copy number variants (CNVs), insertions, deletions, inversions and translocations are poorly covered and may explain some of the missing heritability. The sex chromosomes, often excluded from GWAS studies, may also help explain gender imbalances in CKD. In this review, we outline recent findings on molecular biomarkers for CKD (telomeres, CNVs, mtDNA variants, sex chromosomes) that typically have received less attention than gene polymorphisms. Shorter telomere length has been associated with renal dysfunction and CKD progression, however, most publications report small numbers of subjects with conflicting findings. CNVs have been linked to congenital anomalies of the kidney and urinary tract, posterior urethral valves, nephronophthisis and immunoglobulin A nephropathy. Information on mtDNA biomarkers for CKD comes primarily from case reports, therefore the data are scarce and diverse. The most consistent finding is the A3243G mutation in the MT-TL1 gene, mainly associated with focal segmental glomerulosclerosis. Only one GWAS has found associations between X-chromosome and renal function (rs12845465 and rs5987107). No loci in the Y-chromosome have reached genome-wide significance. In conclusion, despite the efforts to find the genetic basis of CKD, it remains challenging to explain all of the heritability with currently available methods and datasets. Although additional biomarkers have been investigated in less common suspects such as telomeres, CNVs, mtDNA and sex chromosomes, hidden heritability in CKD remains elusive, and more comprehensive approaches, particularly through the integration of multiple -"omics" data, are needed.

Pharmacogenetic polymorphisms contributing to toxicity induced by methotrexate in the southern Spanish population with rheumatoid arthritis

Abstract Rheumatoid arthritis (RA) is a common illness of global significance for public health. Methotrexate (MTX) is the most broadly used disease-modifying antirheumatic drug for the treatment of RA, but it displays marked person-to-person variation in its propensity for toxicity. Several studies have suggested that polymorphisms in methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, reduced folate carrier (RFC1) G80A, and ABCB1 C3435T, could be related to methotrexate toxicity. This prospective study examined the different frequencies of MTHFR, RFC1, and ABCB1 pharmacogenetic variations between patients who have RA and those without RA. We also sought to assess the association between these polymorphisms and MTX toxicity. Four single-nucleotide polymorphisms (SNPs) were genotyped: C677T and A1298C from MTHFR, G80A from RFC1, and C3435T from ABCB1. The efficacy and toxicity of MTX were evaluated through clinical follow-up during 1 year of treatment. RA patients showed a higher frequency of the T allele at MTHFR C677T than patients without RA (p=0.049). There was a significant association between the presence of both the T allele at MTHFR C677T (p=0.006), and the C allele at ABCB1 C3435T (p=0.046), with toxicity development after 12 months of MTX treatment. However, there was no correlation between MTX toxicity and either the A allele at MTHFR A1298C or the G allele at RFC1 A80G. These data suggest that the presence of the MTHFR C677T and ABCB1 C3435T SNPs contribute to MTX toxicity in patients with RA. These observations contribute to a rapidly-growing knowledge base on the pharmacogenetics of RA and personalized medicine.

Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease

Chronic kidney disease (CKD) is an aging-related disorder that represents a major global public health burden. Current biochemical biomarkers, such as serum creatinine and urinary albumin, have important limitations when used to identify the earliest indication of CKD or in tracking the progression to more advanced CKD. These issues underline the importance of finding and testing new molecular biomarkers that are capable of successfully meeting this clinical need. The measurement of changes in nature and/or levels of proteins and metabolites in biological samples from patients provide insights into pathophysiological processes. Proteomic and metabolomic techniques provide opportunities to record dynamic chemical signatures in patients over time. This review article presents an overview of the recent developments in the fields of metabolomics and proteomics in relation to CKD. Among the many different proteomic biomarkers proposed, there is particular interest in the CKD273 classifier, a urinary proteome biomarker reported to predict CKD progression and with implementation potential. Other individual non-invasive peptidomic biomarkers that are potentially relevant for CKD detection include type 1 collagen, uromodulin and mucin-1. Despite the limited sample sizes and variability of the metabolomics studies, some metabolites such as trimethylamine N-oxide, kynurenine and citrulline stand out as potential biomarkers in CKD.

Genetic associations between genes in the renin-angiotensin-aldosterone system and renal disease: a systematic review and meta-analysis

BACKGROUND

Chronic kidney disease (CKD) is defined by abnormalities in kidney structure and/or function present for more than 3 months. Worldwide, both the incidence and prevalence rates of CKD are increasing. The renin-angiotensin-aldosterone system (RAAS) regulates fluid and electrolyte balance through the kidney. RAAS activation is associated with hypertension, which is directly implicated in causation and progression of CKD. RAAS blockade, using drugs targeting individual RAAS mediators and receptors, has proven to be renoprotective.

OBJECTIVES

To assess genomic variants present within RAAS genes, ACE, ACE2, AGT, AGTR1, AGTR2 and REN, for association with CKD.

DESIGN AND DATA SOURCES

A systematic review and meta-analysis of observational research was performed to evaluate the RAAS gene polymorphisms in CKD using both PubMed and Web of Science databases with publication date between the inception of each database and 31 December 2018. Eligible articles included case-control studies of a defined kidney disease and included genotype counts.

ELIGIBILITY CRITERIA

Any paper was removed from the analysis if it was not written in English or Spanish, was a non-human study, was a paediatric study, was not a case-control study, did not have a renal disease phenotype, did not include data for the genes, was a gene expression-based study or had a pharmaceutical drug focus.

RESULTS

A total of 3531 studies were identified, 114 of which met the inclusion criteria. Genetic variants reported in at least three independent publications for populations with the same ethnicity were determined and quantitative analyses performed. Three variants returned significant results in populations with different ethnicities at p<0.05: ACE insertion, AGT rs699-T allele and AGTR1 rs5186-A allele; each variant was associated with a reduced risk of CKD development.

CONCLUSIONS

Further biological pathway and functional analyses of the RAAS gene polymorphisms will help define how variation in components of the RAAS pathway contributes to CKD.

Genetic and clinical biomarkers of tocilizumab response in patients with rheumatoid arthritis

The aim of this study was to investigate the influence of clinical and genetic factors on response to tocilizumab (TCZ) response, remission, low disease activity (LDA) and DAS28 improvement. A retrospective cohort study in 79 RA patients treated with TCZ during 6/18 months of therapy was conducted. CD69(rs11052877), GALNT18(rs4910008), CLEC2D(rs1560011), KCNMB1(rs703505), ENOX1(rs9594987), rs10108210, and rs703297 gene polymorphisms, identified in a recent GWAS as putative predictors of TCZ response, were analysed. Variables independently associated to satisfactory EULAR response at 6 months were GALNT18-CC genotype (ORCC/T-:12.8; CI95%:1.5,108.7; p=0.02), CD69 gene polymorphism (ORAA/GG:17.2; CI95%:2.5,119.6; p=0.004) and lower number of previous biological therapy, BT (OR: 0.45; CI95%:0.3, 0.7; p=0.001). The factors independently associated to higher remission were lower number of previous BT (OR:0.56; CI95%:0.38, 0.82; p=0.003), and GALNT18 CC genotype (ORCT/CC:0.09; CI95%:0.02,0.45;p=0.004; ORTT/CC:0.14; CI95%:0.02,0.79; p=0.026). The A-allele of CD69 (ORA_/GG:6.68;CI95%:1.68,26.51;p=0.007) and lower number of previous BT (OR:0.50; CI95%:0.32,0.77; p=0.002) were independent factors capable to predict higher LDA rates at 6 months. Independent factors associated to higher improvement in DAS28 at 6 months were CD69-AA genotype (B=-0.56; CI95%:-1.09, -0.03; p=0.039), GALNT18-CC genotype (B=-0.88;CI95%:-1.49, -0.27; p=0.005), subcutaneous administration (B=1.03; CI95%:0.44,1.62; p=0.001) and higher baseline DAS28 (B=0.82; CI95%:0.59, 1.05; p=4.9×10(-10)). Lower number of previous BT was the only independent predictor of satisfactory EULAR response (OR:0.60; CI95%:0.34,0.88; p=0.010) and higher remission (OR:0.65; CI95%:0.46,0.93; p=0.018) at 18 months. The C-allele of GALNT18 (ORC-/TT:4.60; CI95%:1.16, 18.27; p=0.03) and lower number of previous BT (OR:0.47; CI95%:0.29,0.74; p=0.001) were independent factors capable to predict higher LDA rates at 18 months. In conclusion, RA patients treated with TCZ showed better EULAR response, remission, LDA and DAS28 improvement rates in patients carrying the GALNT18 C-allele or the CD69 A-allele, particularly when lower number of BT were previously administered.

Genomic approaches in the search for molecular biomarkers in chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is recognised as a global public health problem, more prevalent in older persons and associated with multiple co-morbidities. Diabetes mellitus and hypertension are common aetiologies for CKD, but IgA glomerulonephritis, membranous glomerulonephritis, lupus nephritis and autosomal dominant polycystic kidney disease are also common causes of CKD.

MAIN BODY

Conventional biomarkers for CKD involving the use of estimated glomerular filtration rate (eGFR) derived from four variables (serum creatinine, age, gender and ethnicity) are recommended by clinical guidelines for the evaluation, classification, and stratification of CKD. However, these clinical biomarkers present some limitations, especially for early stages of CKD, elderly individuals, extreme body mass index values (serum creatinine), or are influenced by inflammation, steroid treatment and thyroid dysfunction (serum cystatin C). There is therefore a need to identify additional non-invasive biomarkers that are useful in clinical practice to help improve CKD diagnosis, inform prognosis and guide therapeutic management.

CONCLUSION

CKD is a multifactorial disease with associated genetic and environmental risk factors. Hence, many studies have employed genetic, epigenetic and transcriptomic approaches to identify biomarkers for kidney disease. In this review, we have summarised the most important studies in humans investigating genomic biomarkers for CKD in the last decade. Several genes, including UMOD, SHROOM3 and ELMO1 have been strongly associated with renal diseases, and some of their traits, such as eGFR and serum creatinine. The role of epigenetic and transcriptomic biomarkers in CKD and related diseases is still unclear. The combination of multiple biomarkers into classifiers, including genomic, and/or epigenomic, may give a more complete picture of kidney diseases.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

BACKGROUND

Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

RESULTS

To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

CONCLUSIONS

Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Liquid biopsy in early stage lung cancer

Lung cancer is the leading cause of cancer-associated deaths worldwide. Surgery is the standard treatment for early-stage non-small cell lung cancer (NSCLC). However, 30% to 80% of these patients will die within 5 yearS of diagnosis. Circulating cell-free DNA (cfDNA) harbors pathologic characteristics of the original tumor, such as gene mutations or epigenetic alterations. Analysis of cfDNA has revolutionized the clinical care of advanced lung cancer patients undergoing targeted therapies. However, the low concentration of cfDNA in the blood of early-stage NSCLC patients has hampered its use for management of early disease. Continuing development of more specific and sensitive techniques for detection and analysis of cfDNA will soon enable its leverage in early stage and, perhaps, even screening settings. Therefore, cfDNA analysis may become a tool used for routine NSCLC diagnosis and for monitoring tumor burden, as well as for identifying hidden residual disease. In this review, we will focus on the current evidence of cfDNA in patients with early-stage NSCLC, new and upcoming approaches to identify circulating-tumor biomarkers, their clinical applications and future directions.

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Pharmacogenetics of platinum-based chemotherapy: impact of DNA repair and folate metabolism gene polymorphisms on prognosis of non-small cell lung cancer patients

Chemotherapy based on platinum compounds is the standard treatment for NSCLC patients with EGFR wild type, and is also used as second line in mutated EGFR patients. Nevertheless, this therapy presents poor clinical outcomes. ERCC1, ERCC2, XRCC1, MDM2, MTHFR, MTR, and SLC19A1 gene polymorphisms may contribute to individual variation in response and survival to platinum-based chemotherapy. The aim of this study was to investigate the influence of these polymorphisms on response and survival of NSCLC patients treated with platinum-based chemotherapy. A retrospective-prospective cohorts study was conducted, including 141 NSCLC patients. Polymorphisms were analyzed by PCR real-time with Taqman® probes. Patients with ERCC1 rs3212986-GG (p = 0.0268; OR = 2.50; CI_95% = 1.12-5.69) and XRCC1 rs25487-GG (p = 0.0161; OR = 2.99; CI_95% = 1.26-7.62) genotype showed significantly better ORR. Cox survival analysis revealed that patients carrying the MDM2 rs1690924-GG genotype (p = 0.0345; HR = 1.99; CI_95% = 1.05-3.80) presented higher risk of death. Furthermore, carriers of MTR rs1805087-A alleles (p = 0.0060; HR = 8.91; CI_95% = 1.87-42.42) and SLC19A1 rs1051266-AA genotype (p = 0.0130; HR = 1.74; CI_95% = 1.12-2.68) showed greater risk of progression. No influence of ERCC1 rs11615, ERCC2 rs13181, ERCC2 rs1799793, XRCC1 rs1799782, MDM2 rs1470383, MTHFR rs1801131, and MTHFR rs1801133 on platinum-based chemotherapy clinical outcomes was found. In conclusion, our results suggest that ERCC1 rs3212986, XRCC1 rs25487, MDM2 rs1690924, MTR rs1805087, and SLC19A1 rs1051266 gene polymorphisms may significantly act as predictive factors in NSCLC patients treated with platinum-based chemotherapy.

Effect of CYP4F2, VKORC1, and CYP2C9 in Influencing Coumarin Dose: A Single-Patient Data Meta-Analysis in More Than 15,000 Individuals

The cytochrome P450 (CYP)4F2 gene is known to influence mean coumarin dose. The aim of the present study was to undertake a meta-analysis at the individual patients level to capture the possible effect of ethnicity, gene-gene interaction, or other drugs on the association and to verify if inclusion of CYP4F2*3 variant into dosing algorithms improves the prediction of mean coumarin dose. We asked the authors of our previous meta-analysis (30 articles) and of 38 new articles retrieved by a systematic review to send us individual patients' data. The final collection consists of 15,754 patients split into a derivation and validation cohort. The CYP4F2*3 polymorphism was consistently associated with an increase in mean coumarin dose (+9% (95% confidence interval (CI) 7-10%), with a higher effect in women, in patients taking acenocoumarol, and in white patients. The inclusion of the CYP4F2*3 in dosing algorithms slightly improved the prediction of stable coumarin dose. New pharmacogenetic equations potentially useful for clinical practice were derived.

MET: a new promising biomarker in non-small-cell lung carcinoma

Non-small-cell lung cancer (NSCLC) leads cancer-related deaths worldwide. Mutations in the kinase domain of the EGFR gene provide sensitivity to tyrosine kinase inhibitors (TKI) drugs. TKI show initial response rates over 75% in mutant EGFR-NSCLC patients, although most of these patients acquire resistance to EGFR inhibitors after therapy. EGFR-TKI resistance mechanisms include amplification in MET and its ligand, and also MET mutations. MET signaling dysregulation has been involved in tumor cell growth, survival, migration and invasion, angiogenesis and activation of several pathways, therefore representing an attractive target for anticancer drug development. In this review, we will discuss MET-related mechanisms of EGFR-TKI resistance in NSCLC, as well as the main drugs targeted to inhibit MET pathway.

Pharmacogenetics role in the safety of acenocoumarol therapy

Vitamin K antagonists (VKAs) remain as the most prescribed drug for treatment and prevention of thrombotic disorders in many countries, despite the recent approval of the new oral anticoagulants (NOACs). Although effectiveness and safety of VKAs are tightly associated to maintaining the patient within the international normalised ratio (INR) therapeutic range (TWR), they have been likened to NOACs when patients are in good INR control (≥66% of TWR). Therefore, assessing the safety of patients should be a priority in the selection of the anticoagulation therapy. The aim of this study was to evaluate the association between CYP2C9*2, CYP2C9*3, VKORC1, CYP4F2*3, ABCB1 C3435T, APOE, CYP2C19*2 and CYP2C19*17 gene polymorphisms and treatment safety in 128 patients diagnosed with atrial fibrillation or venous thromboembolism during the initial first seven months of acenocoumarol therapy. After the first month, VKORC1-T-allele and APOE-E3/E3 genotype were independently associated to higher time above therapeutic range (TAR) and lower time below the therapeutic range (TBR). After seven months, VKORC1 T-allele predicted higher TAR, and was also associated to increased INR>4, particularly the TT-genotype (odds ratio [OR]: 32; 95% confidence interval [CI95%]: 6-175; p=810⁻⁵). C-alleles for CYP2C9*3 (OR: 5.5; CI95%: 1.8-17; p=0.003) and ABCB1 (OR: 8.9;CI95%: 1.1-70; p=0.039) independently influenced on INR>6 . Patients VKORC1-TT/ABCB1-C remained 26.8% [19.7-38.9] TAR, with associated relative risk (RR) for INR>4 1.8 higher (CI95%: 1.2-2.5; p=0.015). Patients VKORC1-TT also presented the highest risk of bleeding events (RR: 3.5;CI95%: 1.4-8.4; p=0,010). In conclusion, VKORC1, CYP2C9*3, APOE and ABCB1 genotypes should be considered in prevention of overanticoagulation and bleeding events in the initiation of acenocoumarol therapy.

Interleukins as new prognostic genetic biomarkers in non-small cell lung cancer

BACKGROUND

Surgery is the standard treatment for early-stage NSCLC, and platinum-based chemotherapy remains as the treatment of choice for advanced-stage NSCLC patients with naïve EGFR status. However, overall 5-years relative survival rates are low. Interleukins (ILs) are crucial for processes associated with tumor development. In NSCLC, IL1B, IL6, IL12A, IL13 and IL16 gene polymorphisms may contribute to individual variation in terms of patient survival. The purpose of this study was to evaluate the association between IL gene polymorphisms and survival in NSCLC patients.

METHODS

A prospective cohorts study was performed, including 170 NSCLC patients (114 Stage IIIB-IV, 56 Stage I-IIIA). IL1B (C > T; rs1143634), IL1B (C > T; rs12621220), IL1B (C > G; rs1143623), IL1B (A > G; rs16944), IL1B (C > T; rs1143627), IL6 (C > G; rs1800795), IL12A (C > T; rs662959), IL13 (A > C; rs1881457) and IL16 (G > T; rs7170924) gene polymorphisms were analyzed by PCR Real-Time.

RESULTS

Patients with IL16 rs7170924-GG genotype were in higher risk of death (p = 0.0139; HR = 1.82; CI_95% = 1.13-2.94) Furthermore, carriers of the TT genotype for IL12A rs662959 presented higher risk of progression in the non-resected NSCLC patient subgroup (p = 0.0412; HR = 4.49; CI_95% = 1.06-18.99). The rest of polymorphisms showed no effect of on outcomes.

CONCLUSIONS

Our results suggest that IL16 rs7170924-GG and IL12A rs662959-TT genotypes predict higher risk of death and progression, respectively, in NSCLC patients. No influence of IL1B rs12621220, IL1B rs1143623, IL1B rs16944, IL1B rs1143627, IL6 rs1800795, IL13 rs1881457 on NSCLC clinical outcomes was found in our patients.

Molecular biomarkers in colorectal carcinoma

Colorectal cancer is a tumor with increasing incidence which represents one of the first leading causes of death worldwide. Gene alterations described for colorectal cancer include genome instability (microsatellite and chromosomal instability), CpG islands methylator phenotype, microRNA, histone modification, protein biomarkers, gene mutations (RAS, BRAF, PI3K, TP53, PTEN) and polymorphisms (APC, CTNNB1, DCC). In this article, biomarkers with prognostic value commonly found in colorectal cancer will be reviewed.

The Challenges of Chromosome Y Analysis and the Implications for Chronic Kidney Disease

The role of chromosome Y in chronic kidney disease (CKD) remains unknown, as chromosome Y is typically excluded from genetic analysis in CKD. The complex, sex-specific presentation of CKD could be influenced by chromosome Y genetic variation, but there is limited published research available to confirm or reject this hypothesis. Although traditionally thought to be associated with male-specific disease, evidence linking chromosome Y genetic variation to common complex disorders highlights a potential gap in CKD research. Chromosome Y variation has been associated with cardiovascular disease, a condition closely linked to CKD and one with a very similar sexual dimorphism. Relatively few sources of genetic variation in chromosome Y have been examined in CKD. The association between chromosome Y aneuploidy and CKD has never been explored comprehensively, while analyses of microdeletions, copy number variation, and single-nucleotide polymorphisms in CKD have been largely limited to the autosomes or chromosome X. In many studies, it is unclear whether the analyses excluded chromosome Y or simply did not report negative results. Lack of imputation, poor cross-study comparability, and requirement for separate or additional analyses in comparison with autosomal chromosomes means that chromosome Y is under-investigated in the context of CKD. Limitations in genotyping arrays could be overcome through use of whole-chromosome sequencing of chromosome Y that may allow analysis of many different types of genetic variation across the chromosome to determine if chromosome Y genetic variation is associated with CKD.

Novel BRAFI599Ins Mutation Identified in a Follicular Variant of a Papillary Thyroid Carcinoma: A Molecular Modeling Approach

OBJECTIVE

BRAF mutations are the most common genetic alteration found in papillary thyroid carcinoma (PTC). Approximately, 90% correspond to BRAFV600E, although other less common BRAF mutations have been described. The aim of this study was to describe a new mutation on BRAF gene discovered on the previous thyroid cytology of a patient diagnosed with a follicular variant of PTC (FV-PTC).

METHODS

The mutation was identified by independent cloning of the 2 alleles and direct sequencing in the previous cytology and tumor tissue samples from a patient diagnosed with FV-PTC. To elucidate the effect of the mutation on the structure and hence on the activating mechanism of the protein, the structures of BRAFI599Ins, BRAFT599Ins, BRAFV599Ins and BRAFV600E were modeled by using the reconstructed wild-type BRAF (BRAFWT) crystal structure.

RESULTS

The novel mutation in BRAF consisted in the in-frame insertion of 3 nucleotides (TAA) after nucleotide 1795, resulting in the incorporation of an extra isoleucine residue at position 599 (BRAFI599Ins) of the protein. The structural comparison of BRAFI599Ins, BRAFT599Ins, BRAFV599Ins with BRAFWT, and BRAFV600E models revealed that the overall shape of the kinase was conserved in the protein produced by this novel mutation, except for the displacement of the activation loop (A-loop), as a direct consequence of the increase in loop size, and the exposition of 1 of the 2 residues involved in BRAF activation (T599), probably facilitating its phosphorylation.

CONCLUSION

BRAFI599Ins mutation constitutes a new BRAF mutation affecting the length of the A-loop, which most likely facilitates BRAF activation by altering the A-loop conformation.

De novo resistance biomarkers to anti-HER2 therapies in HER2-positive breast cancer

Therapies targeting HER2 receptor, overexpressed in 20% breast cancer (BC), improved prognosis, however ~62% patients experiment progression during the first year. Molecular mechanisms proposed to be responsible for this de novo resistance include HER2 modifications, defects in the antibody dependent cellular cytotoxicity or in cell arrest and apoptosis or alterations in HER2 signaling components. This article will review the influence of genetic markers investigated to date as cause of de novo resistance to HER2-targeted drugs in HER2-positive BC patients. Biomarkers like p95HER2, CCND1 and CDC25A have demonstrated clinical relevance and prognostic value in HER2-positive BC patients. However, the prognostic value of most biomarkers investigated to date, such as PIK3CA or AKT1, cannot be fully established yet.

Extrapolation of acenocoumarol pharmacogenetic algorithms

INTRODUCTION

Acenocoumarol (ACN) has a narrow therapeutic range that is especially difficult to control at the start of its administration. Various dosing pharmacogenetic-guided dosing algorithms have been developed, but further work on their external validation is required. The aim of this study was to evaluate the extrapolation of pharmacogenetic algorithms for ACN as an alternative to the development of a specific algorithm for a given population.

MATERIAL AND METHODS

The predictive performance, deviation, accuracy, and clinical significance of five pharmacogenetic algorithms (EU-PACT, Borobia, Rathore, Markatos, Krishna Kumar) were compared in 189 stable ACN patients representing all indications for anticoagulant treatment.

RESULTS

The correlation between the dose predictions of the five pharmacogenetic models ranged from 7.7 to 70.6% and the percentage of patients with a correct prediction (deviation ≤20% from actual ACN dose) ranged from 5.9 to 40.7%. EU-PACT and Borobia pharmacogenetic dosing algorithms were the most accurate in our setting and evidenced the best clinical performance.

CONCLUSIONS

Among the five models studied, the EU-PACT and Borobia pharmacogenetic dosing algorithms demonstrated the best potential for extrapolation.