Mol Diagn Ther. 2021 Dec 14. doi: 10.1007/s40291-021-00567-x. Online ahead of print.

ABSTRACT

On the basis of scientific evidence, information on the option, recommendation or requirement to test for pharmacogenetic or pharmacogenomic biomarkers is incorporated in the Summary of Product Characteristics of an increasing number of drugs in Europe. A screening of the Genetic Testing Registry (GTR) showed that a variety of molecular genetic testing methods is currently offered worldwide in testing services with regard to according drugs and biomarkers. Thereby, among the methodology indicated in the screened GTR category 'Molecular Genetics', next-generation sequencing is applied for identification of the largest proportion of evaluated biomarkers that are relevant for therapeutic management of centrally approved drugs in Europe. However, sufficient information on regulatory clearances, clinical utility, analytical and clinical validity of applied methods is rarely provided.

PMID:34905151 | DOI:10.1007/s40291-021-00567-x

Lab Chip. 2021 Dec 14. doi: 10.1039/d1lc00564b. Online ahead of print.

ABSTRACT

Single-nucleotide polymorphism (SNP) plays a critical role in personalized medicine, forensics, pharmacogenetics, and disease diagnostics. Among different existing SNP genotyping techniques, melting curve analysis (MCA) becomes increasingly popular due to its high accuracy and straightforward procedures in extracting the melting temperature (Tm). Yet, its study on existing digital microfluidic (DMF) platforms has intrinsic limitations due to the temperature inhomogeneity within a thickened droplet during the on-chip rapid heating process. Although the utilization of an on-chip thermostat can regulate and monitor the dynamic melting process in real time, the limited Tm accuracy resulting from the insufficient system response time to accommodate the fast-melting evolution still poses a great challenge for precise MCA with high throughput. This work proposes a one-shot MCA on a DMF platform. The tailoring of a functional substrate with hierarchical micro/nano structure enables high-resolution patterning of pL-scale droplets. Specifically, the hydrothermal and photocatalysis treatment allows the functional substrate to exhibit a superwettability contrast of >170°, facilitating passive isolation of the pL-scale DNA sample into highly-resolved pL droplets above the 200 μm superhydrophilic patterns. This high-resolution MCA technique can successfully discriminate KRAS gene targets with single-nucleotide mutations in 3 seconds. The high accuracy and consistency in the acquired Tm when compared with off-chip results demonstrate its opportunities for near-patient diagnostics, precision medicines, genetic counseling, and prevention strategies on DMF platforms.

PMID:34904611 | DOI:10.1039/d1lc00564b

Clin Toxicol (Phila). 2021 Dec 14:1-6. doi: 10.1080/15563650.2021.2013494. Online ahead of print.

ABSTRACT

BACKGROUND: The lockdown periods imposed in 2020 by governments had deleterious consequences on population mental health. Several studies based on declarative data have suggested that the lockdown periods were associated with changes in psychoactive substance use but few relied on toxicological analyses.

AIMS: We studied the impact of lockdowns on the pattern of routine care toxicological screening performed on patients hospitalized at the emergency ward (EW) and intensive care units (ICU) at the Grenoble University Hospital.

METHOD: This was a retrospective, monocentric study comparing routine care toxicology biological tests performed in children older than 12 years of age and adults hospitalized at the ICU and EW in 2018, 2019, and 2020. Alcohol, illicit drugs, and medications were screened. Generalized linear models were generated to evaluate the effect of the lockdown periods on toxicology results, considering age and sex.

RESULTS: The study included 13,910 samples from 11,786 patients. There was no significant difference in the repartition of sex or age over the three years. The frequency of positive toxicological tests increased during the lockdown periods (adjusted odds ratio (OR) 95% confidence interval (CI): 1.14, (1.01-1.28), p = .026). The frequency of poly-exposures also rose during these periods (OR 1.43 (1.11-1.82), p = .004) mostly among men (OR 1.54 (1.02-2.04), p = .022), 12-25-year-old patients (OR 1.69 (1.07-2.31), p = .016), and seniors (>56 years) (OR 1.54 (1.00-1.97), p = .032).

CONCLUSIONS: This study suggests that lockdown episodes were associated with increased incidence of psychoactive substance poly-exposures, highlighting the need for preventive strategies for high-risk populations.

PMID:34904494 | DOI:10.1080/15563650.2021.2013494

Arthritis Care Res (Hoboken). 2021 Dec 13. doi: 10.1002/acr.24834. Online ahead of print.

ABSTRACT

OBJECTIVE: To test the ability of machine learning (ML) approaches with clinical and genomic biomarkers to predict methotrexate treatment response in patients with early rheumatoid arthritis (RA).

METHODS: Demographic, clinical and genomic data from 643 patients of European ancestry with early RA (mean age 54 years; 70% female) subdivided into a training (n=336) and validation cohort (n=307) were used. The genomic data comprised 160 single nucleotide polymorphisms (SNPs) previously associated with RA or methotrexate metabolism. Response to methotrexate monotherapy was defined as good or moderate by the European League Against Rheumatism (EULAR) response criteria at 3-month follow-up. Supervised ML methods were trained with 5-repeats and 10-fold cross-validation using the training cohort. Prediction performance was validated in the independent validation cohort.

RESULTS: Supervised ML methods combining age, sex, smoking, rheumatoid factor, baseline Disease Activity Score with 28-joint count (DAS28) and 160 SNPs predicted EULAR response at 3 months with the area under the receiver operating curve of 0.84 (p=0.05) in the training cohort and achieved a prediction accuracy of 76% (p=0.05) in the validation cohort (sensitivity 72%, specificity 77%). Intergenic SNPs rs12446816, rs13385025, rs113798271, and ATIC (rs2372536) had variable importance above 60.0 and along with baseline DAS28 were among the top predictors of methotrexate response.

CONCLUSION: Pharmacogenomic biomarkers combined with baseline DAS28 can be useful in predicting response to methotrexate in patients with early RA. Applying ML to predict treatment response holds promise for guiding effective RA treatment choices, including timely escalation of RA therapies. This article is protected by copyright. All rights reserved.

PMID:34902228 | DOI:10.1002/acr.24834

Methods Mol Biol. 2022;2401:263-271. doi: 10.1007/978-1-0716-1839-4_17.

ABSTRACT

Microarrays are broadly used in the omic investigation and have several areas of applications in biology and medicine, providing a significant amount of data for a single experiment. Different kinds of microarrays are available, identifiable by characteristics such as the type of probes, the surface used as support, and the method used for the target detection. To better deal with microarray datasets, the development of microarray data analysis protocols simple to use as well as able to produce accurate reports, and comprehensible results arise. The object of this paper is to provide a general protocol showing how to choose the best software tool to analyze microarray data, allowing to efficiently figure out genomic/pharmacogenomic biomarkers.

PMID:34902134 | DOI:10.1007/978-1-0716-1839-4_17

Methods Mol Biol. 2022;2401:13-27. doi: 10.1007/978-1-0716-1839-4_2.

ABSTRACT

Pharmacogenomics is an important research field that studies the impact of genetic variation of patients on drug responses, looking for correlations between single nucleotide polymorphisms (SNPs) of patient genome and drug toxicity or efficacy. The large number of available samples and the high resolution of the instruments allow microarray platforms to produce huge amounts of SNP data. To analyze such data and find correlations in a reasonable time, high-performance computing solutions must be used. Cloud4SNP is a bioinformatics tool, based on Data Mining Cloud Framework (DMCF), for parallel preprocessing and statistical analysis of SNP pharmacogenomics microarray data.This work describes how Cloud4SNP has been extended to execute applications on Apache Spark, which provides faster execution time for iterative and batch processing. The experimental evaluation shows that Cloud4SNP is able to exploit the high-performance features of Apache Spark, obtaining faster execution times and high level of scalability, with a global speedup that is very close to linear values.

PMID:34902119 | DOI:10.1007/978-1-0716-1839-4_2

Methods Mol Biol. 2022;2401:1-12. doi: 10.1007/978-1-0716-1839-4_1.

ABSTRACT

The understanding of the biological differences which underlie the inter-individual variability in drug response improved the efficacy of cancer therapy in the era of precision medicine. In fact molecularly targeted drugs and immunotherapy represent a revolution in cancer treatment. The identification of genetic predictive and/or prognostic biomarkers linked to drug pharmacokinetics (PK) and pharmacodynamics (PD) is allowed by the development of high-throughput omics tools for detecting and understanding biological differences among individuals, in order to improve drug efficacy and minimize risk of toxicity. Personalized medicine in cancer treatment reduces costs of the healthcare system. Unfortunately, pharmacogenomics biomarkers discovery is influenced by complexity, need of high-quality evidence, and a validation process for regulatory purposes. This chapter is focused on the critic analysis of presently available pharmacogenomics tools for discovering or testing genetic polymorphic variants in drug metabolizing enzyme to be introduced in clinical practice for the prospective stratification of cancer patients.

PMID:34902118 | DOI:10.1007/978-1-0716-1839-4_1

J Diabetes Metab Disord. 2021 Sep 14;20(2):1513-1519. doi: 10.1007/s40200-021-00894-0. eCollection 2021 Dec.

ABSTRACT

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that is associated with elevated blood glucose levels. Sulfonylureas (SFUs) are the most widely used among the oral antidiabetic drugs that are highly metabolized by cytochrome P450 family 2 subfamily C member 9 (CYP2C9). The CYP2C9 has been shown to be associated with a better glycemic response to SFUs and a lower treatment failure rate. The aim of the present study was to assess the influence of the CYP2C9 rs1067910 gene variant on the SFUs response in a group of Iranian patients for the first time.

METHODS: Blood samples were taken from 30 patients with T2DM under sulfonylurea treatment. DNA extraction was performed using Salting out method, and then genotyping was performed by polymerase chain reaction (PCR) followed by Sanger sequencing.

RESULTS: There was no significant difference in the fasting blood sugar (FBS) between T2DM patients with different genotypes before and after the treatment with SFUs (P = 0.073 and P = 0.893, respectively). Although HbA1c was significantly different among AA, CA and CC carriers before (P = 0.001) and after (P = 0.018) treatment, no significant change was observed after treatment in all three groups.

CONCLUSIONS: In the present study based on only 30 samples in pilot survey, it is shown that the therapeutic response to SFUs was not related to rs1057910 CYP2C9 variant.

PMID:34900803 | PMC:PMC8630254 | DOI:10.1007/s40200-021-00894-0

J Diabetes Metab Disord. 2021 Aug 10;20(2):1407-1413. doi: 10.1007/s40200-021-00874-4. eCollection 2021 Dec.

ABSTRACT

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a metabolic disorder in which the patients with high blood sugar develop insufficient insulin secretion or insulin resistance. The solute carrier family, 5 member 2 (SLC5A2) gene is a member of sodium/glucose transporter family which can reduce heart and kidney problems. The current study aims to look into any association between rs11646054 variant in SLC5A2 gene and the anti-diabetic efficacy and safety of empagliflozin.

METHODS: 14 T2DM who failed to respond to previous treatments, empagliflozin 10 mg was added for 6 months. Genotyping of the rs11646054 variant of SLC5A2 gene was performed by polymerase chain reaction (PCR) followed by Sanger sequencing.

RESULTS: Although hemoglobin A1c (HbA1c) and low-density lipoprotein (LDL) were not significantly different, but the mean fasting blood sugar (FBS), 2-h post prandial (2hpp), albumin-to-creatinine ratio (ACR), and total cholesterol (TC) were significantly decreased after 6 months empagliflozin treatment. There was a significant difference in the mean final reductions in FBS level among genotypes. It's important to mention that those who were GG homozygotes had a tendency to have more decrements.

CONCLUSIONS: The study results indicate that effects of variation in SLC5A2 (rs11646054) on the clinical efficacy of empagliflozin were negligible.

PMID:34900792 | PMC:PMC8630276 | DOI:10.1007/s40200-021-00874-4

Acta Pharm Sin B. 2021 Nov;11(11):3406-3416. doi: 10.1016/j.apsb.2021.02.003. Epub 2021 Feb 10.

ABSTRACT

Non-small cell lung cancer is recognized as the deadliest cancer across the globe. In some areas, it is more common in women than even breast and cervical cancer. Its rise, vaulted by smoking habits and increasing air pollution, has garnered much attention and resource in the medical field. The first lung cancer treatments were developed more than half a century ago. Unfortunately, many of the earlier chemotherapies often did more harm than good, especially when they were used to treat genetically unsuitable patients. With the introduction of personalized medicine, physicians are increasingly aware of when, how, and in whom, to use certain anti-cancer agents. Drugs such as tyrosine kinase inhibitors, anaplastic lymphoma kinase inhibitors, and monoclonal antibodies possess limited utility because they target specific oncogenic mutations, but other drugs that target mechanisms universal to all cancers do not. In this review, we discuss many of these non-oncogene-targeting anti-cancer agents including DNA replication inhibitors (i.e., alkylating agents and topoisomerase inhibitors) and cytoskeletal function inhibitors to highlight their application in the setting of personalized medicine as well as their limitations and resistance factors.

PMID:34900526 | PMC:PMC8642451 | DOI:10.1016/j.apsb.2021.02.003

Front Pharmacol. 2021 Nov 26;12:784909. doi: 10.3389/fphar.2021.784909. eCollection 2021.

ABSTRACT

Primaquine, an 8-aminoquinoline, is the only medication approved by the World Health Organization to treat the hypnozoite stage of Plasmodium vivax and P. ovale malaria. Relapse, triggered by activation of dormant hypnozoites in the liver, can occur weeks to years after primary infection, and provides the predominant source of transmission in endemic settings. Hence, primaquine is essential for individual treatment and P. vivax elimination efforts. However, primaquine use is limited by the risk of life-threatening acute hemolytic anemia in glucose-6-phosphate dehydrogenase (G6PD) deficient individuals. More recently, studies have demonstrated decreased efficacy of primaquine due to cytochrome P450 2D6 (CYP2D6) polymorphisms conferring an impaired metabolizer phenotype. Failure of standard primaquine therapy has occurred in individuals with decreased or absent CYP2D6 activity. Both G6PD and CYP2D6 are highly polymorphic genes, with considerable geographic and interethnic variability, adding complexity to primaquine use. Innovative strategies are required to overcome the dual challenge of G6PD deficiency and impaired primaquine metabolism. Further understanding of the pharmacogenetics of primaquine is key to utilizing its full potential. Accurate CYP2D6 genotype-phenotype translation may optimize primaquine dosing strategies for impaired metabolizers and expand its use in a safe, efficacious manner. At an individual level the current challenges with G6PD diagnostics and CYP2D6 testing limit clinical implementation of pharmacogenetics. However, further characterisation of the overlap and spectrum of G6PD and CYP2D6 activity may optimize primaquine use at a population level and facilitate region-specific dosing strategies for mass drug administration. This precision public health approach merits further investigation for P. vivax elimination.

PMID:34899347 | PMC:PMC8661410 | DOI:10.3389/fphar.2021.784909

Front Pharmacol. 2021 Nov 25;12:661443. doi: 10.3389/fphar.2021.661443. eCollection 2021.

ABSTRACT

Tamoxifen (TAM), a selective oestrogen receptor modulator, is one of the most used treatments in oestrogen receptor-positive (ER+) early and metastatic breast cancer (BC) patients. The response to TAM has a high degree of inter-individual variability. This is mainly due to genetic variants in CYP2D6 gene, as well as other genes encoding proteins involved in the TAM pharmacokinetic and/or pharmacodynamic. Therefore, prediction of the TAM response using these genetic factors together with other non-genetic variables may be relevant to improve breast cancer treatment. Thus, in this work, we used genetic polymorphisms and clinical variables for TAM response modelling. One hundred sixty-two ER + BC patients with 2 years of TAM treatment were retrospectively recruited, and the genetic polymorphisms CYP2D6*4, CYP3A4*1B (CYP3A4*1.001), CYP3A5*3, UGT2B7*2, UGT2B15*2, SULT1A1*2, and ESRA V364E were analyzed by PCR-RFLP. Concomitantly, the therapeutic response was obtained from clinical records for association with genotypes using univariate and multivariate biostatistical models. Our results show that UGT2B15*1/*2 genotype protects against relapse (OR = 0.09; p = 0.02), CYP3A5*3/*3 genotype avoids endometrial hyperplasia (OR = 0.07; p = 0.01), SULT1A1*1/*2 genotype avoids vaginal bleeding (OR = 0.09; p = 0.03) and ESRA 364E/364E genotype increases the probability of vaginal bleeding (OR = 5.68; p = 0.02). Logistic regression models, including genomic and non-genomic variables, allowed us to obtain preliminary predictive models to explain relapse (p = 0.010), endometrial hyperplasia (p = 0.002) and vaginal bleeding (p = 0.014). Our results suggest that the response to TAM treatment in ER + BC patients might be associated with the presence of the studied genetic variants in UGT2B15, CYP3A5, SULT1A1 and ESRA genes. After clinical validation protocols, these models might be used to help to predict a percentage of BC relapse and adverse reactions, improving the individual response to TAM-based treatment.

PMID:34899282 | PMC:PMC8656167 | DOI:10.3389/fphar.2021.661443

Ann Hum Genet. 2021 Dec 13. doi: 10.1111/ahg.12453. Online ahead of print.

ABSTRACT

Fluoropyrimidines are chemotherapy drugs that may cause severe adverse events, and their metabolism occurs by dihydropyrimidine deydrogenase (DPD), coded by DPYD. Variants in the DPYD were associated to a greater risk of toxicity. Our aim was to determine the frequency of the most relevant DPYD alleles according to CPIC guidelines (DPYD*2A-rs3918290, DPYD*13-rs55886062, rs67376798, and HapB3-rs75017182) in a sample of 800 healthy Southern Brazilians. Frequencies for rs3918290, rs75017182, and rs67376798 were 0.25%, 1.06%, and 0.38%, respectively. No rs55886062 allele was detected. In total, 3.4% of individuals were classified as intermediate metabolizers. Frequencies for rs3918290, rs55886062, and rs67376798 were similar to those found in non-Finnish Europeans; however, rs75017182 was less frequent when compared to non-Finnish Europeans, but more frequent than in Africans and East Asians. rs3918290 and rs67376798 also presented higher frequency when compared to Africans. The Latino population was the only one that did not differ from our sample in any variant analyzed. The frequencies for all the other populations (non-Finnish European, African, South Asian, and East Asian) presented differences from our sample in at least one variant. rs115232898 was not analyzed in the present study. Cost-effective studies should be performed to evaluate the implementation of these tests in the clinical practice in the Southern Brazil.

PMID:34897655 | DOI:10.1111/ahg.12453

Crit Rev Oncol Hematol. 2021 Dec 8:103567. doi: 10.1016/j.critrevonc.2021.103567. Online ahead of print.

ABSTRACT

The development of innovative technologies and the advances in the genetics and genomics, have offered new opportunities for personalized treatment in oncology. Although the selection of the patient based on the molecular characteristics of the neoplasm has the potential to revolutionize the therapeutic scenario of oncology, this approach is extremely challenging. The access, homogeneity, and economic sustainability of the required genomic tests should be warranted in the clinical practice, as well as the specific scientific and clinical expertise for the choice of medical therapies. All these elements make essential the collaboration of different specialists within the Molecular Tumor Boards (MTBs). In this position paper, based on experts' opinion, the AIOM-SIAPEC/IAP-SIBioC-SIC-SIF-SIGU-SIRM Italian Scientific Societies critically discuss the available molecular profiling technologies, the proposed criteria for the selection of patients candidate for evaluation by the MTB, the criteria for the selection and analysis of biological samples, and the regulatory and pharmaco-economic issues.

PMID:34896250 | DOI:10.1016/j.critrevonc.2021.103567

Therapie. 2021 Nov 25:S0040-5957(21)00248-1. doi: 10.1016/j.therap.2021.11.008. Online ahead of print.

NO ABSTRACT

PMID:34895754 | DOI:10.1016/j.therap.2021.11.008

Trials. 2021 Dec 11;22(1):896. doi: 10.1186/s13063-021-05775-8.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is a common, chronic, debilitating mood disorder that causes serious functional impairment and significantly decreased quality of life. Pharmacotherapy represents the first-line treatment option; however, only approximately one third of patients respond to the first treatment because of the ineffectiveness or side effects of antidepressants. Precision medicine in psychiatry might offer clinicians the possibility to tailor treatment according to the best possible evidence of efficacy and tolerability for each subject. In this context, our study aims to carry out a clinical validation of a combinatorial pharmacogenomics (PGx) test in an Italian MDD patient cohort with advocacy license independence.

METHODS: Our study is a prospective participant- and rater-blinded, randomized, controlled clinical observational trial enrolling 300 MDD patients who are referred to psychiatric services to receive a new antidepressant due to the failure of their current treatment and/or the onset of adverse effects. Eligible participants are randomized to the TGTG group (Treated with Genetic Test Guide) or TAU group (Treated as Usual). For all subjects, DNA is collected with a buccal brush. The primary outcome is the reduction in depressive symptomatology. The secondary outcomes involve a range of scales that assess MDD symptoms and social functioning outcomes. The assessment is performed at four timepoints: baseline and 4, 8, and 12 weeks.

DISCUSSION: This project represents the first randomized controlled clinical trial to investigate whether a non-commercial PGx test improves outcomes in an MDD naturalistic cohort. Moreover, the identification of new genetic variants associated with non-response or side effects will improve the efficacy of the test, leading to further cost-saving.

TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT04615234. Registered on November 4, 2020.

PMID:34895291 | DOI:10.1186/s13063-021-05775-8

Mutat Res Rev Mutat Res. 2021 Jul-Dec;788:108391. doi: 10.1016/j.mrrev.2021.108391. Epub 2021 Jul 17.

ABSTRACT

Breast cancer (BC) is the most frequent neoplasm and one of the main causes of death in women. The pharmacological treatment of BC consists of hormonal therapy, chemotherapeutic agents and targeted therapy. The response to BC therapy is highly variable in clinical practice. This variability can be explained by the presence of genetic polymorphisms in genes involved in the pharmacokinetics, pharmacodynamics or immune response of patients. The abundant evidence of associations between low-activity alleles CYP2D6*3, *4, *5, *6, *10 and *41 and poor results with tamoxifen therapy, and between DPYD gene polymorphisms rs3918290, rs55886062, rs67376798 and rs75017182 and increased risk of toxicity to fluoropyrimidine therapy, justify the existence of clinical pharmacogenetic guidelines. The NQO1 rs1800566 polymorphism is related to poorer results in BC therapy with chemotherapy agents. The polymorphism rs1695 of the GSTP1 gene has been associated with the effectiveness and toxicity of fluorouracil, cyclophosphamide and epirubicin therapy. Finally, the HLA-DQA1*02:01 allele is significantly associated with the occurrence of liver toxicity events in patients receiving lapatinib. There is moderate evidence to support the aforementioned associations and, therefore, a high probability of these being considered as future predictive genetic biomarkers of response. However, further studies are required to reinforce or clarify their clinical relevance.

PMID:34893156 | DOI:10.1016/j.mrrev.2021.108391

Sci Adv. 2021 Dec 10;7(50):eabj4226. doi: 10.1126/sciadv.abj4226. Epub 2021 Dec 10.

ABSTRACT

[Figure: see text].

PMID:34890233 | DOI:10.1126/sciadv.abj4226

Pac Symp Biocomput. 2022;27:385-396.

ABSTRACT

Precision medicine faces many challenges, including the gap of knowledge between disease genetics and pharmacogenomics (PGx). Disease genetics interprets the pathogenicity of genetic variants for diagnostic purposes, while PGx investigates the genetic influences on drug responses. Ideally, the quality of health care would be improved from the point of disease diagnosis to drug prescribing if PGx is integrated with disease genetics in clinical care. However, PGx genes or variants are usually not reported as a secondary finding even if they are included in a clinical genetic test for diagnostic purposes. This happens even though the detection of PGx variants can provide valuable drug prescribing recommendations. One underlying reason is the lack of systematic classification of the knowledge overlap between PGx and disease genetics. Here, we address this issue by analyzing gene and genetic variant annotations from multiple expert-curated knowledge databases, including PharmGKB, CPIC, ClinGen and ClinVar. We further classified genes based on the strength of evidence supporting a gene's pathogenic role or PGx effect as well as the level of clinical actionability of a gene. Twenty-six genes were found to have pathogenic variation associated with germline diseases as well as strong evidence for a PGx association. These genes were classified into four sub-categories based on the distinct connection between the gene's pathogenic role and PGx effect. Moreover, we have also found thirteen RYR1 genetic variants that were annotated as pathogenic and at the same time whose PGx effect was supported by a preponderance of evidence and given drug prescribing recommendations. Overall, we identified a nontrivial number of gene and genetic variant overlaps between disease genetics and PGx, which laid out a foundation for combining PGx and disease genetics to improve clinical care from disease diagnoses to drug prescribing and adherence.

PMID:34890165

Hum Genet. 2021 Dec 10. doi: 10.1007/s00439-021-02397-7. Online ahead of print.

ABSTRACT

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

PMID:34889978 | DOI:10.1007/s00439-021-02397-7