WO2023194369A1

WO2023194369A1 - Genetic markers for severe covid-19

Info

Publication number: WO2023194369A1
Application number: PCT/EP2023/058822
Authority: WO
Inventors: Jaume Marrugat de la Iglesia; Roberto Elosua Llanos; Anna CAMPS VILARÓ; Isaac SUBIRANA CACHINERO; Xavier NOGUES SOLAN; Joan Ramon MASCLANS; Roberto GÜERRI FERNÁNDEZ; Judith MARIN CORRAL; Helena TIZON MARCO; Ramón BRUGADA I TERRADELLES; Mel·lina PINSACH ABUIN; Alexandra PÉREZ SERRA; Rafel RAMOS BLANES; Ruth MARTÍ LLUCH; Irene ROMAN DEGANO
Original assignee: Fundació Institut Mar D'investigacions Mèdiques (Imim); Fundació Institut Universitari Per A La Recerca A L’Atenció Primaria De Salut Jordi Gol I Gurina; Universitat De Girona; Universitat De Vic-Universitat Central De Catalunya; Fundació Institut D'investigació Biomèdica De Girona Dr. Josep Trueta
Priority date: 2022-04-08
Filing date: 2023-04-04
Publication date: 2023-10-12

Abstract

The present application refers to an in vitro method for predicting the risk of a subject to develop severe coronavirus disease 2019 (COVID-19), said method comprising the step of determining, in a sample isolated from the subject, the presence or absence of risk alleles at the following single nucleotide variants (SNVs): rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, wherein the presence of at least one risk allele is indicative of an increased risk of developing severe COVID-19.

Description

Genetic markers for severe COVID-19

This application claims the benefit of European Patent Application 22382342.8 filed April 8th, 2022.

Technical Field

The present application refers to the field of coronavirus disease 2019 and, in particular, to genetic markers to predict the risk of suffering from severe coronavirus disease 2019.

Background Art

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its associated disease (coronavirus disease 2019, or simply COVID-19) reached pandemic level in March 2020. Since then, several waves and new virus variants emerged. As per March 2022, more than 480 million people had been infected, and more than 6 million had died from COVID-19 worldwide.

The development of vaccines against COVID-19 resulted in a significant decrease in the proportion of hospitalizations and mortality. Nevertheless, severe cases continue to leak in hospitals owing to a combination of the limited efficacy of vaccines, the existence of a proportion of unvaccinated population, the emergence of more infective virus variants, and the individual susceptibility and comorbidity.

Clinical presentation of COVID-19 ranges from asymptomatic (40%) to fatal (1 .7%), although most patients experience mild symptoms. COVID-19 severity has been associated with CV and thrombotic complications and with hyperinflammatory syndrome. However, the mechanisms involved in these complications are not fully understood.

Among the symptomatic patients, COVID-19 patients with pre-existing cardiovascular (CV) risk factors, such as older age, male sex, hypertension, obesity, diabetes, chronic disease, among other, or with overt CV disease are at higher risk of severe COVID-19 presentation. Additionally, some genetic variants have been associated with COVID-19 severity. However, despite recent developments, there exists no reliable methods to predict which patients will develop severe COVD-19.

Therefore, there is a need in the art to provide new methods for risk-stratification of COVID-19 patients.

Summary of Invention

The inventors have identified a series of single nucleotide variant (SNV) markers that, when used in combination, are associated with a higher risk of developing severe COVID-19. As shown below, these polymorphic markers appear to show predictive value independently of classical clinical risk factors and significantly improve the predictive value of said classical risk factors when used in combination with them.

The SNVs forming part of the genetic risk signature of the invention are: rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637. The presence of risk alleles in these polymorphic sites has been found to be associated with a higher risk of developing severe COVID-19. In other words, the inventors surprisingly found that these 5 SNVs contribute to predict COVID-19 severity.

Thus, a first aspect of the invention provides an in vitro method for predicting the risk of a subject to develop severe coronavirus disease 2019 (COVID-19), said method comprising the step of determining, in a sample isolated from the subject, the presence or absence of risk alleles at the following single nucleotide variants (SNVs): rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637.

The method of the first aspect of the invention may predict subjects that are at risk of developing severe COVID-19 before they are actually infected. It may also predict the risk of SARS-Cov-2 recently infected patients to develop severe COVID-19. Thus, the method of the invention can also be envisaged as a method for the prognosis of COVID-19, said method comprising the step of determining, for example, in a saliva or blood sample isolated from the subject, the presence or absence of risk alleles at the following SNVs: rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637.

The prediction of the risk of developing severe COVID-19 according to the first aspect of the invention requires determining all of the SNVs defined above, i.e. rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637. However, it suffices that one risk allele is found within said SNVs to determine a higher risk of a subject to suffer from severe COVID-19. Notwithstanding the above, the risk of suffering severe disease increases linearly with increasing number of risk alleles found for that particular subject. Thus, for example, a higher risk is predicted for subjects in whom the presence of at least one risk variant is detected at all of the above SNVs as compared to a subject with none, and also as compared to a subject with two, or three, or four.

A second aspect of the invention refers to means for detecting the presence or absence of risk alleles at the following single nucleotide variants (SNVs): rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, wherein the risk alleles are those disclosed in Table 1.

In a third aspect, the above means form part of a kit. In other words, a third aspect of the invention refers to a kit comprising means for detecting the presence or absence of risk alleles at the following single nucleotide variants (SNVs): rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, wherein the risk alleles are those disclosed in Table 1. A fourth aspect refers to use of means as defined in the second aspect or a kit as defined in the third aspect for predicting the risk of a subject developing severe COVID-19 as defined in the first aspect.

The method of the invention allows for a significantly improved risk-stratification of COVID-19 patients, bringing about relevant advantages in terms of patient management.

Thus, a fifth aspect of the invention refers to an in vitro method for deciding or recommending a medical regime to a subject, said method comprising:

(I) predicting the risk of a subject to develop severe COVID-19 as defined in the first aspect, and (ii) recommending or deciding a medical regime if the subject is predicted to have a high risk of developing severe COVID-19.

A sixth aspect of the invention is the combined use of the following SNVs: rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, and, optionally, of one or more further SNV selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714, and combinations thereof, as a genetic marker for predicting the risk of a subject to develop severe COVID-19. These group of SNVs are also independently related to COVID-19 severity.

An additional aspect of the invention refers to an in vitro method for identifying a patient in need of early and/or aggressive therapy for COVID-19 or in need of prophylactic therapy comprising:

(I) predicting the risk of a subject to develop severe COVID-19 as defined in the first aspect, and (ii) identifying that the subject is in need of early and/or aggressive therapy for COVID-19 or in need of prophylactic therapy when a high risk of severe COVID-19 is determined.

The method of the invention allows for stratification of COVID-19 patients according to their risk of developing severe disease. One last aspect of the invention thus refers to a method for stratifying COVID-19 patients according to their risk of developing severe COVID-19, said method comprising (I) determining the risk of the patients to develop severe COVID-19 as defined in the first aspect, and (ii) stratifying the patients according to the risk determined in (I).

Brief Description of Drawings

Fig. 1 shows the adverse allele distribution of the 5-Single Nucleotide Variant (SNV) risk score in patients with severe (cases; black bars) and non-severe (controls; white bars) COVID-19. Odds ratios (OR) for the association between severe COVID-19 and genetic risk scores (GRSs) are also shown.

Fig. 2 shows the adverse allele distribution of the 10-Single Nucleotide Variant (SNV) risk score in patients with severe (cases; in black columns) and non-severe (controls; in white columns) COVID-19. Odds ratios (OR) for the association between severe COVID-19 and GRSs are also shown.

Detailed description of the invention

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as is commonly understood by one of skill in the art to which this invention belongs at the time of filling. However, in the event of any latent ambiguity, definitions provided herein take precedent over any dictionary or extrinsic definition. Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular.

The term "severe COVID-19”, as used herein, refers generally to the severity of COVID-19 in which patients with SARS-CoV-2 infection suffer from one or more complications selected from the group consisting of a respiratory frequency greater than 30 times per minute, a blood oxygen saturation under 94%, presence of infiltrates in over 50% of pulmonary fields within 24 to 48 hours of symptom onset, pneumonia, required mechanical ventilation, cardiovascular (CV) complications, thrombotic complications, hyperinflammatory syndrome, a ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PaO2/FIO2) <300 mm Hg, respiratory failure, septic shock, multiple organ dysfunction, and death. In particular, severe COVID-19 embodiment is associated with one or more of the above complications, more particularly, more than two or more than three of the above complications.

The term "single nucleotide variant” (SNV) refers to a nucleotide sequence variation occurring when a single nucleotide in the genome or another shared sequence differs between members of species or between paired chromosomes in an individual. A SNV can also be designed as a mutation with low allele frequency in a defined population. SNVs according to the present application may fall within coding sequences of genes, non-coding regions of genes or the intronic regions between genes. A SNV can be a common variant or a rare mutation, and can be germline or somatic. The term SNV encompasses the term "single nucleotide polymorphism” (SNP), which is generally understood to a variant that is present in at least 1% of the population. The SNVs of the present invention can be considered as SNPs and, therefore, the terms SNP and SNV are used herein interchangeably. The term "polymorphism” is also used herein interchangeably with SNP and SNV.

SNVs sometimes exist in linkage disequilibrium. Linkage disequilibrium is the correlation between nearby variants such that the alleles at neighboring polymorphisms (observed on the same chromosome) are associated within a population more often than if they were unlinked. Thus, the invention contemplates determining the disclosed SNPs or, alternatively, those in linkage disequilibrium. For example, rs4830974, which is contemplated as a further SNV to improve the prediction of the risk to develop severe COVID-19 (see below), is in linkage disequilibrium with rs2158082, rs5936011, rs6629110, and rs6632704. In carrying out the method of the invention, it is contemplated that any of these variants in linkage disequilibrium be used as an alternative to rs4830974.

The terms "predicting the risk” and "determining whether a subject has an altered/increased risk", as used herein, relates to the assessment of the probability according to which a subject is going to suffer from a disease. As will be understood by those skilled in the art, such an assessment, although preferred to be, may usually not be correct for 100% of the subjects to be diagnosed or evaluated. The term, however, requires that a statistically significant portion of subjects can be identified as having an increased risk. Whether a portion is statistically significant can be determined without further ado by the person skilled in the art using various well known statistic evaluation tools, e.g., determination of confidence intervals, p-value determination, Student's t- test, Mann-Whitney test, etc. This is performed according to methods well known to the skilled person. Preferred confidence intervals are at least 50%, at least 60%, at least 70%, at least 80%, at least 90% at least 95%. The p-values are, preferably, 0.2, 0.1 or 0.05.

The term "risk allele”, as used herein, refers generally to the allele that confers a higher risk of developing severe COVID-19. An allele is a variation of the sequence of nucleotides that encodes the synthesis of a gene product at the same place on a DNA molecule. An allele can be based on a single nucleotide variant (SNV), it can be based on differences up to several thousand base-pairs long.

The term "prognosis" as used herein refers to a prediction of the probable course and outcome of an already diagnosed clinical condition or disease. A prognosis of a patient is usually made by evaluating factors, markers, and/or symptoms of a disease that are indicative of a favourable or unfavourable course or outcome of the disease.

The term "Genetic Risk Score” (GRS) as used herein, refers generally to an estimate of the cumulative contribution of genetic factors to a specific outcome of interest in an individual. The score may take into account the reported effect sizes for those alleles and may be normalized by adjusting for the total number of risk alleles and effect sizes evaluated.

The term "area under the curve” (AUG) as used herein describes the receiver operating characteristic (ROC) curve or the area under the ROC curve. AUG is involved in the specificity and sensitivity of biomarkers. A perfect marker (AUC=1.0) produces a point or a point of coordinates (0,1) in the upper left corner of the ROC space, which means sensitivity is 100% (no false negative) and specificity is 100% (no false positives)).

The term "p value" relates to the probability of obtaining test results at least as extreme as the results actually observed, under the assumption that the null hypothesis is actually true, i.e. there is no difference between the mean values of the different groups. The smaller the p-value, the higher the probability that the substitution hypothesis can better explain the observation than the null hypothesis, i.e. the alternative hypothesis is more likely to be true. The term "odds ratio” (OR) as used herein refers to a measure of association between an exposure and an outcome. The OR represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure. An odds ratio of 1 implies that the event is equally likely in both groups. An odds ratio greater than 1 implies that the outcome has a higher probability to occur given the particular exposure.

Confidence Interval (Cl) as used herein refers to the plain meaning known to one of ordinary skill in the art. The confidence interval refers to a statistical range with a specified probability that a given parameter lies within the range.

In the present invention, the term "genetic marker" is understood as a SNV (or SNP) which can be determined in a biological sample from a patient by standard methods (including those disclosed herein), and is predictive or denotes a condition of the patient from which the sample was obtained.

In its more general concept, the invention refers to an in vitro method for predicting the risk of a subject to develop severe coronavirus disease 2019 (COVID-19), which comprises the step of determining, in a sample isolated from the subject, the presence or absence of risk alleles at different single nucleotide variants (SNVs). These SNVs being rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637. These SNVs are further defined in table 1.

Table 1. 5 SNVs and risk alleles

BH, Benjamini-Hochberg method; Chr, chromosome; Cl, confidence interval; MAF, minor allele frequency;

OR, odds ratio; RAF, risk allele frequency; SNV, single nucleotide variant. In a particular embodiment, the method can be used for predicting the risk of a healthy subject to develop severe COVID-19 in case he/she got infected by the severe acute respiratory coronavirus 2 (SARS-CoV-2). In another embodiment, the method can be used for predicting the risk of a patient already diagnosed with COVID-19 to develop severe COVID-19. In a particular embodiment of the first aspect, the method is for the prognosis of COVID-19. In other words, the present invention refers to an in vitro method for predicting the risk of a subject to develop COVID-19-related complications.

In another embodiment of the first aspect, the risk alleles at the different SNVs are those disclosed in Table 1 .

In one embodiment of the first aspect, the presence of at least two risk alleles from those disclosed in table 1 is indicative of an increased risk of developing severe COVID-19. In a particular embodiment, the presence of at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or ten risk alleles is indicative of increased risk of developing severe COVID-19.

In one embodiment of the first aspect, the identification of at least 2, at least 3, at least 4, or at least 5 SNVs containing a risk allele is indicative of increased risk of developing severe COVID-19. In a particular embodiment, a high risk of severe COVID-19 is predicted when the presence of a risk allele is detected at each of the SNVs. In a more particular embodiment, a high risk of severe COVID-19 is predicted when detecting the presence of the alleles AAA at rs11385942, G at rs12190287, T at rs1746048, A at rs13109457, and A at rs17465637 (table 1).

In a particular embodiment of the first aspect, severe COVID-19 comprises a complication selected from the group consisting of respiratory frequency >30 times/min, blood oxygen saturation <93%, presence of infiltrates in >50% of pulmonary fields within 24 to 48 hours of symptom onset, pneumonia, required mechanical ventilation, cardiovascular complications, thrombotic complications, hyperinflammatory syndrome, death, and combinations thereof.

Additional SNVs may be used to further enhance or complement the risk prediction of the first aspect of the invention. For example, the method may further comprise determining the presence or absence of risk alleles at one of the SNVs selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714, and combinations thereof. These SNVs are further defined in Table 2. In a particular embodiment, the risk alleles to be determined are those disclosed in Table 2.

Table 2. SNVs and risk alleles

OR, odds ratio; RAF, risk allele frequency; SNV, single nucleotide variant.

In one embodiment, at least one further SNV from those disclosed in table 2 is assessed. In particular embodiments, at least two, at least three, at least four, or at least 5 further SNVs are assessed. In one embodiment, the presence of at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or ten further risk alleles is indicative of increased risk of developing severe COVID-19. In one embodiment, identification of at least 3, at least 4, or at least 5 further SNVs containing a risk allele is indicative of increased risk of developing severe COVID-19. In a particular embodiment, a high risk of severe COVID-19 is predicted when the presence of a risk allele is detected at each of the further SNVs. In a more particular embodiment, a high risk of severe COVID-19 is predicted when further detecting the presence of the alleles A at rs1801020, G at rs4961252, A at rs4830974, T at rs2246833, and C at rs75885714.

In an even more particular embodiment, a high risk of severe COVID-19 is predicted when detecting the presence of the alleles AAA at rs11385942, G at rs12190287, T at rs1746048, A at rs13109457, A at rs17465637, A at rs1801020, G at rs4961252, A at rs4830974, T at rs2246833, and C at rs75885714.

In another particular embodiment, the odds of developing severe COVID-19 is proportional to the number of risk alleles present in the sample.

In another embodiment of the first aspect, the method further comprises determining the presence or absence of risk alleles at a SNV selected from the group consisting of rs2158082, rs5936011, rs6629110, rs6632704, as an alternative to rs4830974. These SNVs are further defined in Table 3. In a particular embodiment, the risk alleles to be determined are those disclosed in Table 3.

The term "sample", as used herein, refers to any sample from a biological source and includes, without limitation, cell cultures or extracts thereof, biopsied material obtained from a mammal or extracts thereof, and blood, saliva, urine, feces, semen, tears, or other body fluids or extracts thereof. In a particular embodiment, the method as defined in the first aspect comprises a sample obtained from the subject which is a tissue or a bodily fluid sample (e.g., blood, plasma, serum, ascitic fluid, bronco-alveolar lavage, urine, breath, stool, CFS, saliva). In particular embodiments, the sample is a biological fluid. In more particular embodiments, the sample is selected from blood, plasma, serum, oral tissue, oral scraping, oral wash, saliva, sweat er urine. In a more particular embodiment, the sample is blood or saliva.

Table 3. SNVs and risk alleles

OR, odds ratio; RAF, risk allele frequency; SNV, single nucleotide variant.

Those skilled in the art will readily recognize that the analysis of the nucleotides present according to the method of the invention in an individual's nucleic acid can be done by any method or technique capable of determining nucleotides present in a polymorphic site. As it is obvious in the art the nucleotides present in the polymorphic markers can be determined from either nucleic acid strand or from both strands.

Once a biologic sample from a subject has been obtained (e.g., a bodily fluid, such as urine, saliva, plasma, serum, or a tissue sample, such as buccal tissue sample or buccal cell) detection of a sequence variation or allelic variant SNV is typically undertaken. Virtually any method known to the skilled artisan is employed. Perhaps the most direct method is to actually determine the sequence of either genomic DNA or cDNA and compare these sequences to the known alleles SNVs of the gene. This can be a fairly expensive and timeconsuming process. Nevertheless, this technology is quite commonly and is well known.

Other possible commercially available methods exist for the high throughput SNP identification not using direct sequencing technologies. For example, Illumina's Veracode Technology, Taqman® SNP Genotyping Chemistry and KASPar SNP genotyping Chemistry.

A variation on the direct sequence determination method is the Gene Chip(TM) method available from Affymetrix. Alternatively, robust and less expensive ways of detecting DNA sequence variation are also commercially available. For example, Perkin Elmer adapted its TAQman Assay(TM) to detect sequence variation. Orchid BioSciences has a method called SNP- IT (TM). (SNP-ldentification Technology) that uses primer extension with labeled nucleotide analogs to determine which nucleotide occurs at the position immediately 3' of an oligonucleotide probe, the extended base is then identified using direct fluorescence, indirect colorimetric assay, mass spectrometry, or fluorescence polarization. Sequenom uses a hybridization capture technology plus MALDI-TOF (Matrix Assisted Laser Desorption/lonization— Time-of-Flight mass spectrometry) to detect SNP genotypes with their MassARRAY(TM) system. Promega provides the READIT(TM) SNP/Genotyping System (U.S. Pat. No. 6,159,693). In this method, DNA or RNA probes are hybridized to target nucleic acid sequences. Probes that are complementary to the target sequence at each base are depolymerized with a proprietary mixture of enzymes, while probes which differ from the target at the interrogation position remain intact. The method uses pyrophosphorylation chemistry in combination with luciferase detection to provide a highly sensitive and adaptable SNP scoring system. Third Wave Technologies has the Invader OS(TM) method that uses a proprietary Cleavaseg enzymes, which recognize and cut only the specific structure formed during the Invader process. Invader OS relies on linear amplification of the signal generated by the Invader process, rather than on exponential amplification of the target. The Invader OS assay does not utilize PCR in any part of the assay. In addition, there are a number of forensic DNA testing labs and many research labs that use gene-specific PCR, followed by restriction endonuclease digestion and gel electrophoresis (or other size separation technology) to detect restriction fragment length polymorphisms (RFLPs).

In various embodiments of the first aspect of the invention, the presence or absence of the SNVs is identified by amplifying or failing to amplify an amplification product from the sample. Polynucleotide amplifications are typically template-dependent. Such amplifications generally rely on the existence of a template strand to make additional copies of the template. Primers are short nucleic acids that are capable of priming the synthesis of a nascent nucleic acid in a template-dependent process, which hybridize to the template strand. Typically, primers are from ten to thirty base pairs in length, but longer sequences can be employed. Primers may be provided in double-stranded and/or single-stranded form, although the single-stranded form generally is preferred. Often, pairs of primers are designed to selectively hybridize to distinct regions of a template nucleic acid, and are contacted with the template DNA under conditions that permit selective hybridization. Depending upon the desired application, high stringency hybridization conditions may be selected that will only allow hybridization to sequences that are completely complementary to the primers. In other embodiments, hybridization may occur under reduced stringency to allow for amplification of nucleic acids containing one or more mismatches with the primer sequences. Once hybridized, the template-primer complex is contacted with one or more enzymes that facilitate template-dependent nucleic acid synthesis. Multiple rounds of amplification, also referred to as "cycles," are conducted until a sufficient amount of amplification product is produced.

A number of template dependent processes are available to amplify the oligonucleotide sequences present in a given template sample. One of the best known amplification methods is the polymerase chain reaction. In PCR, pairs of primers that selectively hybridize to nucleic acids are used under conditions that permit selective hybridization. The term primer, as used herein, encompasses any nucleic acid that is capable of priming the synthesis of a nascent nucleic acid in a template-dependent process. Primers may be provided in double-stranded or single-stranded form, although the single-stranded form is preferred. Primers are used in any one of a number of template dependent processes to amplify the target gene sequences present in a given template sample. One of the best known amplification methods is PCR, which is well known for the skilled person. In PCR, two primer sequences are prepared which are complementary to regions on opposite complementary strands of the target-gene(s) sequence. The primers will hybridize to form a nucleic- acid:primer complex if the target-gene(s) sequence is present in a sample. An excess of deoxyribonucleoside triphosphates is added to a reaction mixture along with a DNA polymerase, e.g., Taq polymerase, that facilitates template-dependent nucleic acid synthesis. If the target-gene(s) sequence:primer complex has been formed, the polymerase will cause the primers to be extended along the target-gene(s) sequence by adding on nucleotides. By raising and lowering the temperature of the reaction mixture, the extended primers will dissociate from the target-gene(s) to form reaction products, excess primers will bind to the target-gene(s) and to the reaction products and the process is repeated. These multiple rounds of amplification, referred to as "cycles", are conducted until a sufficient amount of amplification product is produced.

The amplification product may be digested with a restriction enzyme before analysis. In still other embodiments of any of the above aspects, the presence or absence of the SNP is identified by hybridizing the nucleic acid sample with a primer labeled with a detectable moiety. In other embodiments of any of the above aspects, the detectable moiety is detected in an enzymatic assay, radioassay, immunoassay, or by detecting fluorescence. In other embodiments of any of the above aspects, the primer is labeled with a detectable dye (e.g., SYBR Green I, YO-PRO-I, thiazole orange, Hex, pico green, edans, fluorescein, FAM, or TET). In other embodiments of any of the above aspects, the primers are located on a chip. In other embodiments of any of the above aspects, the primers for amplification are specific for said SNVs.

Another method for amplification is the ligase chain reaction ("LCR"). LCR differs from PCR because it amplifies the probe molecule rather than producing amplicon through polymerization of nucleotides. In LCR, two complementary probe pairs are prepared, and in the presence of a target sequence, each pair will bind to opposite complementary strands of the target such that they abut. In the presence of a ligase, the two probe pairs will link to form a single unit. By temperature cycling, as in PCR, bound ligated units dissociate from the target and then serve as "target sequences" for ligation of excess probe pairs. U.S. Pat. No. 4,883,750, incorporated herein by reference, describes a method similar to LCR for binding probe pairs to a target sequence.

An isothermal amplification method, in which restriction endonucleases and ligases are used to achieve the amplification of target molecules that contain nucleotide 5'-[[alpha]-thio]-triphosphates in one strand of a restriction site also may be useful in the amplification of nucleic acids in the present invention. In one embodiment, loop-mediated isothermal amplification (LAMP) method is used for single nucleotide polymorphism (SNP) typing.

Strand Displacement Amplification (SDA) is another method of carrying out isothermal amplification of nucleic acids, which involves multiple rounds of strand displacement and synthesis, i.e., nick translation. A similar method, called Repair Chain Reaction (RCR), involves annealing several probes throughout a region targeted for amplification, followed by a repair reaction in which only two of the four bases are present. The other two bases can be added as biotinylated derivatives for easy detection. Other nucleic acid amplification procedures include transcription-based amplification systems, including nucleic acid sequence based amplification. In nucleic acid sequence based amplification, the nucleic acids are prepared for amplification by standard phenol/chloroform extraction, heat denaturation of a clinical sample, treatment with lysis buffer and minispin columns for isolation of DNA and RNA or guanidinium chloride extraction of RNA. These amplification techniques involve annealing a primer, which has target specific sequences. Following polymerization, DNA/RNA hybrids are digested with RNase H while double stranded DNA molecules are heat denatured again. In either case, the single stranded DNA is made fully double stranded by addition of second target specific primer, followed by polymerization. The double-stranded DNA molecules are then multiply transcribed by a polymerase such as T7 or SP6. In an isothermal cyclic reaction, the RNA's are reverse transcribed into double stranded DNA, and transcribed once against with a polymerase such as T7 or SP6. The resulting products, whether truncated or complete, indicate target specific sequences.

Other amplification methods may be used in accordance with the present invention. In one embodiment, "modified" primers are used in a PCR-like, template and enzyme dependent synthesis. The primers may be modified by labeling with a capture moiety (e.g., biotin) and/or a detector moiety (e.g., enzyme). In the presence of a target sequence, the probe binds and is cleaved catalytically. After cleavage, the target sequence is released intact to be bound by excess probe. Cleavage of the labeled probe signals the presence of the target sequence. In another approach, a nucleic acid amplification process involves cyclically synthesizing single-stranded RNA ("ssRNA"), ssDNA, and double-stranded DNA (dsDNA), which may be used in accordance with the present invention. The ssRNA is a first template for a first primer oligonucleotide, which is elongated by reverse transcriptase (RNA-dependent DNA polymerase). The RNA is then removed from the resulting DNA:RNA duplex by the action of ribonuclease H (RNase H, an RNase specific for RNA in duplex with either DNA or RNA). The resultant ssDNA is a second template for a second primer, which also includes the sequences of an RNA polymerase promoter (exemplified by T7 RNA polymerase) 5' to its homology to the template. This primer is then extended by DNA polymerase (exemplified by the large "Klenow" fragment of E. coll DNA polymerase I), resulting in a double-stranded DNA ("dsDNA") molecule, having a sequence identical to that of the original RNA between the primers and having additionally, at one end, a promoter sequence. This promoter sequence can be used by the appropriate RNA polymerase to make many RNA copies of the DNA. These copies can then re-enter the cycle leading to very swift amplification. With proper choice of enzymes, this amplification can be done isothermally without addition of enzymes at each cycle. Because of the cyclical nature of this process, the starting sequence can be chosen to be in the form of either DNA or RNA.

It may be desirable to separate nucleic acid products from other materials, such as template and excess primer. In one embodiment, amplification products are separated by agarose, agarose-acrylamide or polyacrylamide gel electrophoresis using standard methods (Sambrook et al., 1989). Separated amplification products may be cut out and eluted from the gel for further manipulation. Using low melting point agarose gels, the separated band may be removed by heating the gel, followed by extraction of the nucleic acid. Separation of nucleic acids may also be effected by chromatographic techniques known in art. There are many kinds of chromatography which may be used in the practice of the present invention, including adsorption, partition, ion-exchange, hydroxyapatite, molecular sieve, reverse-phase, column, paper, thin-layer, and gas chromatography as well as HPLC. In certain embodiments, the amplification products are visualized. A typical visualization method involves staining of a gel with ethidium bromide and visualization of bands under UV light. Alternatively, if the amplification products are integrally labeled with radio- or fluorometrically- labeled nucleotides, the separated amplification products can be exposed to x-ray film or visualized with light exhibiting the appropriate excitatory spectra.

Alternatively, the presence of the polymorphic positions according to the method of the invention can be determined by hybridisation or lack of hybridisation with a suitable nucleic acid probe specific for a polymorphic nucleic acid but not with the non-mutated nucleic acid. By "hybridize" is meant to form a doublestranded molecule between complementary polynucleotide sequences, or portions thereof, under various conditions of stringency. For example, stringent salt concentration will ordinarily be less than about 750 mM NaCI and 75 mM trisodium citrate, preferably less than about 500 mM NaCI and 50 mM trisodium citrate, and more preferably less than about 250 mM NaCI and 25 mM trisodium citrate. Low stringency hybridization can be obtained in the absence of organic solvent, e.g., formamide, while high stringency hybridization can be obtained in the presence of at least about 35% formamide, and more preferably at least about 50% formamide. Stringent temperature conditions will ordinarily include temperatures of at least about 30°C, more preferably of at least about 37°C, and most preferably of at least about 42°C. Varying additional parameters, such as hybridization time, the concentration of detergent, e.g., sodium dodecyl sulfate (SDS), and the inclusion or exclusion of carrier DNA, are well known to those skilled in the art. Various levels of stringency are accomplished by combining these various conditions as needed. In a preferred embodiment, hybridization will occur at 30°C in 750 mM NaCI, 75 mM trisodium citrate, and 1% SDS. In a more preferred embodiment, hybridization will occur at 37°C in 500 mM NaCI, 50 mM trisodium citrate, 1% SDS, 35% formamide, and 100 [mu]g/ml denatured salmon sperm DNA (ssDNA). In a most preferred embodiment, hybridization will occur at 42°C in 250 mM NaCI, 25 mM trisodium citrate, 1% SDS, 50% formamide, and 200 [mu]g/ml ssDNA. Useful variations on these conditions will be readily apparent to those skilled in the art.

For most applications, washing steps that follow hybridization will also vary in stringency. Wash stringency conditions can be defined by salt concentration and by temperature. As above, wash stringency can be increased by decreasing salt concentration or by increasing temperature. For example, stringent salt concentration for the wash steps will preferably be less than about 30 mM NaCI and 3 mM trisodium citrate, and most preferably less than about 15 mM NaCI and 1.5 mM trisodium citrate. Stringent temperature conditions for the wash steps will ordinarily include a temperature of at least about 25°C, more preferably of at least about 42°C, and even more preferably of at least about 68°C. In a preferred embodiment, wash steps will occur at 25°C in 30 mM NaCI, 3 mM trisodium citrate, and 0.1% SDS. In a more preferred embodiment, wash steps will occur at 42°C in 15 mM NaCI, 1.5 mM trisodium citrate, and 0.1% SDS. In a more preferred embodiment, wash steps will occur at 68°C in 15 mM NaCI, 1.5 mM trisodium citrate, and 0.1% SDS. Additional variations on these conditions will be readily apparent to those skilled in the art. Hybridization techniques are well known to those skilled in the art.

Nucleic acid molecules useful for hybridization in the methods of the invention include any nucleic acid molecule which exhibits substantial identity so as to be able to specifically hybridize with the target nucleic acids. Polynucleotides having "substantial identity" to an endogenous sequence are typically capable of hybridizing with at least one strand of a double-stranded nucleic acid molecule. By "substantially identical" is meant a polypeptide or nucleic acid molecule exhibiting at least 50% identity to a reference amino acid sequence or nucleic acid sequence. Preferably, such a sequence is at least 60%, more preferably 80% or 85%, and more preferably 90%, 95% or even 99% identical at the amino acid level or nucleic acid to the sequence used for comparison. Sequence identity is typically measured using sequence analysis software (for example, Sequence Analysis Software Package of the Genetics Computer Group, University of Wisconsin Biotechnology Center, 1710 University Avenue, Madison, Wis. 53705, BLAST, BESTFIT, GAP, or PILEUP/PRETTYBOX programs). Such software matches identical or similar sequences by assigning degrees of homology to various substitutions, deletions, and/or other modifications. Conservative substitutions typically include substitutions within the following groups: glycine, alanine, valine, isoleucine, leucine, aspartic acid, glutamic acid, asparagine, glutamine, serine, threonine, lysine, arginine, phenylalanine, and tyrosine. In an exemplary approach to determining the degree of identity, a BLAST program may be used, with a probability score between e<"3> and e<"100> indicating a closely related sequence.

A detection system may be used to measure the absence, presence, and amount of hybridization for all of the distinct sequences simultaneously. Preferably, a scanner is used to determine the levels and patterns of fluorescence.

Thus, in particular embodiments, the presence or absence of the risk alleles is carried out by hybridization of a nucleotide probe. In particular, wherein the probe contains a detectable label. And more in particular, the method comprises a previous step of amplifying the region where the SNV is located and, optionally, digesting the amplification product with a restriction enzyme.

Another particular embodiment, is that in which the method comprises the determination of the presence or absence of the risk alleles which is carried out by a method comprising the following steps:

Genomic DNA extraction from the samples using an adequate method;

Optionally, a pre-amplification;

Genotyping of DNA samples using an adequate genotyping technology such as the TaqMan® SNP following manufacturer's instructions;

Fluorescence data collection with proper readers, such as Fluidigm EP1 Reader, which at the end of the PGR reaction, the fluorescent signal for the two reporter dyes is measured. The ratio of the signals will be indicative for the genotype of the sample; and

Data analysis to obtain genotype calls using adequate software, such as Fluidigm SNV Genotyping Analysis Software.

In a particular embodiment of the first aspect, the method refers to a method for predicting the risk of a subject aged between 35 to 85 years to develop severe COVID-19. In particular embodiments, the subjects are aged 35 to 45 years. It has been found that the method of the invention better predicts risk of severe COVID-19 in patients younger than 45 years.

In a particular embodiment of the first aspect, the method further comprises computing a Genetic Risk Score (GRS). In a more particular embodiment, the GRS is computed as the unweighted count of risk alleles of the independent SNVs (0, 1 or 2), and in men, SNPs on the X chromosome are counted as 0 or 2. In other words, the GRS can be defined as the number of risk alleles at the non-sexual chromosomes plus the number of risk alleles of the X chromosome in women, or plus the number of risk alleles of the X chromosome multiplied by 2 in men.

In particular embodiments, the risk probability to develop severe COVID-19 can be calculated by multiplying the GRS of a subject by a determined coefficient, herein termed "genetic risk regression coefficient” or "GRS regression coefficient”. Said coefficient is related to the odds ratio (OR), herein termed "GRS odds ratio” or "GRS OR”, which is understood as a statistic that quantifies the strength of the association between the two events, i.e. presence of risk alleles and severe COVID-19. In particular, the "genetic risk regression coefficient” is calculated as a Logistic Regression Coefficient. It can also be calculated as the natural logarithm of the GRS OR (Log(GRS OR)).

In one embodiment, the GRS odds ratio computed with the selection of the 5 SNVs disclosed in Table 1 is 1.06 (95%CI: 1.04-1.07) per risk allele. That is a GRS regression coefficient of 0.05826 per risk allele, which means that with these 5 SNVs GRS, every detected risk allele increases the risk probability of developing severe COVID-19 of a subject by 6% (95% Cl: 4-7%).

In a particular embodiment, we also claim that the 5 SNVs GRS associated risk is modulated by age. Thus, on one hand in a subject aged 35 to 45 years old, the GRS odds ratio computed with the selection of the 5 SNVs disclosed in Table 1 is 1.08 (95%CI: 1.05-1.11) per risk allele. That is a GRS regression coefficient of 0.07696 per risk allele, which means that with the 5 SNVs GRS, every detected risk allele increases the odds of developing severe COVID-19 of a subject aged 35 to 45 years old by 8% (95% Cl: 5-11%). On the other hand, in a subject aged 75 to 84 years old, the GRS odds ratio computed with the selection of the 5 SNVs disclosed in Table 1 is 1.03 (95%CI: 1.01-1.06) per risk allele. That is a GRS regression coefficient of 0.02956 per risk allele, which means that with the 5 SNVs GRS, every detected risk allele increases the odds of developing severe COVID-19 of a subject aged 75 to 84 years old by 3% (95% Cl: 1-6%).

In a particular embodiment, the GRS odds ratio computed with the selection of the 10 SNVs disclosed in Table 1 and Table 2 is 1.04 (95%CI: 1.03-1.05) per risk allele. That is a GRS regression coefficient of 0.03922 per risk allele, which means that with these 10 SNVs GRS, every detected risk allele increases the probability of severe COVID-19 by 4% (95% Cl: 3-5%).

In a particular embodiment, we also claim that the 10 SNVs GRS associated risk is modulated by age. Thus, on one hand, in a subject aged 35 to 45 years old, the GRS odds ratio computed with the selection of the 10 SNVs disclosed in Table 1 and Table 2 is 1.06 (95%CI: 1.05-1.08) per risk allele. That is a GRS regression coefficient of 0.05826 per risk allele, which means that with these 10 SNVs GRS, every detected risk allele increases the odds of developing severe COVID-19 of a subject aged 35 to 45 years old by 6% (95% Cl: 5- 8%). On the other hand, in a subject aged 75 to 84 years old, the GRS odds ratio computed with the selection of the 10 SNVs disclosed in Table 1 is 1.02 (95%CI: 1.01-1.03) per risk allele. That is a GRS regression coefficient of 0.01980 per risk allele, which means that with the 10 SNVs GRS, every detected risk allele increases the odds of developing severe COVID-19 of a subject aged 75 to 84 years old by 2% (95% Cl: 1- 3%).

In a particular embodiment, the risk probability to develop severe COVID-19 can be adjusted with other constants. In a particular embodiment, the AUG of the risk probability calculation considering the 5 SNVs of table 1 is 0.60 (0.58-0.62). In a particular embodiment, the AUG of the risk probability calculation for the 10 SNVs of table 1 and table 2 is 0.61 (0.59-0.64)

Table 4. Risk prediction models 3 and 4

AUG, Area under the curve; Cl, confidence interval; DBP, Diastolic blood pressure; GRS, genetic risk score; RLRC, Rounded Logistic Regression Coefficient

Other known genetic markers, biomarkers and/or any other risk factors associated to COVID-19 severity may be used to improve the risk prediction.

In another embodiment of the first aspect, the method further comprises determining additional factors from the subject such as age, sex, smoking status, diabetes, hypertension, total cholesterol, high density lipoprotein (HDL)-cholesterol level, body mass index. In particular embodiments, additional risk factors may be considered. Other factors that may be considered are pre-existing cardiovascular (CV) risk factors, such as male sex, chronic kidney disease, systolic blood pressure, diastolic blood pressure, glycaemia, high density lipoprotein, low density lipoprotein (LDL)-cholesterol level, triglycerides, glomerular filtration rate, renal insufficiency, left ventricular hypertrophy, alcohol consumption history, smoking history, exercise history, diet, family history of cardiovascular disease or disorder, coronary artery disease risk, history of heart failure, history of coronary artery disease, history of stroke, history of thrombosis, history of neoplasia, history of immune disease, history of COPD, history of mental/cognitive illness, and overt CV disease. These other risk factors are from now on termed as non-genetic risk factors.

In another embodiment, the method further comprises computing a model for determining the risk of a subject to develop severe COVID-19 considering the GRS and additional non-genetic risk factors as described above. Said non-genetic risk factors OR and regression coefficients are determined for every model.

For example, a risk odds to develop severe COVID-19 can be calculated for a subject by using the following formula:

Log(odds) = (GRS*genetic risk regression coefficient) + E(non-genetic risk factor*non-genetic risk factor regression coefficient)

The non-genetic risk odds and the genetic risk regression coefficients may vary depending on the number of SNVs used to compute the GRS (see table 5). Thus, in particular embodiments the risk regression coefficients for both genetic and non-genetic risk factors are those defined in table 5 in the columns Rounded Logistic Regression Coefficients (RLRC).

In another embodiment, the risk odds and probability of a subject to develop severe COVID-19 can be calculated using an algorithm based on the GRS and the additional non-genetic risk factors as described above adjusted according to their coefficients and optionally applying further adjustments and/or constants. In a particular embodiment, for example using the following formula:

Log(odds) = constant + (GRS*GRS regression coefficient) + E(non-genetic risk factor*non-genetic risk factor regression coefficient)

Table 5. Risk prediction models 0, 1 and 2 including genetic and non-genetic risk factors

Models 1 and 2 included the variables of Model 0 plus the GRS. NRI is showing the reclassification of Models 1 and 2 compared to Model 0. * Interaction, t Odds ratio per 10 units. AIC, Akaike information criterion; AUG,

Area under the curve; Cl, confidence interval; DBP, Diastolic blood pressure; GRS, genetic risk score; NRI, net reclassification index; SBP, Systolic blood pressure; SNV, single nucleotide variant; RLRC, Rounded Logistic Regression Coefficient A second aspect of the invention refers to means for detecting the presence or absence of risk alleles at the following SNVs: rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, wherein the risk alleles are those disclosed in Table 1 . In a one embodiment of the second aspect, the means further comprise means for detecting the presence or absence of risk alleles at a SNV selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714, and combinations thereof. In a particular embodiment, the risk alleles are those disclosed in Table 1 and Table 2. In a particular embodiment of the second aspect, the means further comprise means for detecting the presence or absence of risk alleles at a SNV selected from the group consisting of rs2158082, rs5936011, rs6629110, rs6632704, and combinations thereof. In a particular embodiment, the risk alleles are those disclosed in Table 1, Table 2, and Table 3.

A person skilled in the art will recognize that, based on the SNV and/or associated sequence information disclosed herein, detection reagents can be developed and used to assay any SNV of the present invention individually or in combination, and such detection reagents can be readily incorporated into one of the established kit or system formats which are well known in the art. The kits may further comprise a questionnaire or measurement of classical clinical factors.

The terms "kits", as used herein in the context of SNP detection reagents, are intended to refer to objects or devices containing combinations of multiple SNP detection reagents, or one or more SNP detection reagents in combination with one or more other types of elements or components (e.g., other types of biochemical reagents, containers, packages such as packaging intended for commercial sale, substrates to which SNP detection reagents are attached, electronic hardware components, etc.). Accordingly, the present invention further provides SNP detection kits and systems, including but not limited to, packaged probe and primer sets (e.g., TaqMan probe/primer sets), arrays/microarrays of nucleic acid molecules, and beads that contain one or more probes, primers, or other detection reagents for detecting one or more SNVs of the present invention. The kits/systems can optionally include various electronic hardware components; for example, arrays ("DNA chips") and microfluidic systems ("lab-on-a-chip" systems) provided by various manufacturers typically comprise hardware components. Other kits/systems (e.g., probe/primer sets) may not include electronic hardware components, but may be comprised of, for example, one or more SNP detection reagents (along with, optionally, other biochemical reagents) packaged in one or more containers.

In some embodiments, a SNP detection kit typically contains one or more detection reagents and other components (e.g., a buffer, enzymes such as DNA polymerases or ligases, chain extension nucleotides such as deoxynucleotide triphosphates, and in the case of Sanger-type DNA sequencing reactions, chain terminating nucleotides, positive control sequences, negative control sequences, and the like) necessary to carry out an assay or reaction, such as amplification and/or detection of a SNP-containing nucleic acid molecule. A kit may further contain means for determining the amount of a target nucleic acid, and means for comparing the amount with a standard, and can comprise instructions for using the kit to detect the SNP- containing nucleic acid molecule of interest. In one embodiment of the present invention, kits are provided which contain the necessary reagents to carry out one or more assays to detect one or more SNVs disclosed herein. In a preferred embodiment of the present invention, SNP detection kits/systems are in the form of nucleic acid arrays, or compartmentalized kits, including microfluidic/lab-on-a-chip systems. SNP detection kits/systems may contain, for example, one or more probes, or pairs of probes, that hybridize to a nucleic acid molecule at or near each target SNP position. Multiple pairs of allele-specific probes may be included in the kit/system to simultaneously assay large numbers of SNPs, at least one of which is a SNP of the present invention. In some kits/systems, the allele-specific probes are immobilized to a substrate such as an array or bead. For example, the same substrate can comprise allele-specific probes for detecting at least 1; 10; 100; 1000; 10,000; 100,000; 500,000 (or any other number in-between) or substantially all of the SNVs disclosed herein.

Preferably, the kit comprises several oligonucleotides that will hybridize specifically to the nucleic acid sequences defined in Table 1, Table 2, and/or Table 3 or to sequences flanking said regions. These oligonucleotides will enable specific amplification of the polynucleotide wherein the polymorphic position is to be assessed from a human genomic DNA or cDNA template, using PCR. Most preferably, these oligonucleotides will also enable specific genotyping of these polymorphic sites by acting as primers, probes, or ligation substrates that enable differentiation of polymorphic alleles. Alternatively, these oligonucleotides may be suitable for use in methods that do not depend on prior amplification of the starting DNA, such as Invader assays and ligation-based detection methods. Preferably, the oligonucleotides or other kit components will include a detectable label, e.g., a fluorescent label, enzyme label, light scattering label, mass label, or other label. Alternatively, detection may be achieved by RFLP methods. In addition, the kit may include a plurality of different nucleic acid sequences allowing detection of nucleic acid sequences or gene products corresponding to different polymorphisms as defined in Table 1, Table 2, and Table 3. The kit may also optionally contain instructions for use, which can include a listing of the polymorphisms correlating with a particular treatment or treatments for a disease or diseases and/or a statement or listing of the diseases for which a particular polymorphism or polymorphisms correlates with a treatment efficacy and/or safety.

The terms "arrays," "microarrays," and "DNA chips" are used herein interchangeably to refer to an array of distinct polynucleotides affixed to a substrate, such as glass, plastic, paper, nylon or other type of membrane, filter, chip, or any other suitable solid support. The polynucleotides can be synthesized directly on the substrate, or synthesized separately from the substrate and then affixed to the substrate.

Any number of probes, such as allele-specific probes, may be implemented in an array, and each probe or pair of probes can hybridize to a different SNP position. In the case of polynucleotide probes, they can be synthesized at designated areas (or synthesized separately and then affixed to designated areas) on a substrate using a light-directed chemical process. Each DNA chip can contain, for example, thousands to millions of individual synthetic polynucleotide probes arranged in a grid-like pattern and miniaturized (e.g., to the size of a dime). Preferably, probes are attached to a solid support in an ordered, addressable array.

A microarray can be composed of a large number of unique, single-stranded polynucleotides fixed to a solid support. Typical polynucleotides are preferably about 6-60 nucleotides in length, more preferably about 15-30 nucleotides in length, and most preferably about 18-25 nucleotides in length. For certain types of microarrays or other detection kits/systems, it may be preferable to use oligonucleotides that are only about 7-20 nucleotides in length. In other types of arrays, such as arrays used in conjunction with chemiluminescent detection technology, preferred probe lengths can be, for example, about 15-80 nucleotides in length, preferably about 50-70 nucleotides in length, more preferably about 55-65 nucleotides in length, and most preferably about 60 nucleotides in length. The microarray or detection kit can contain polynucleotides that cover the known 5 ' or 3' sequence of the target SNP site, sequential polynucleotides that cover the full-length sequence of a gene/transcript; or unique polynucleotides selected from particular areas along the length of a target gene/transcript sequence, particularly areas corresponding to one or more SNVs disclosed herein. Polynucleotides used in the microarray or detection kit can be specific to a SNP or SNPs of interest (e.g., specific to a particular SNP allele at a target SNP site, or specific to particular SNP alleles at multiple different SNP sites), or specific to a polymorphic gene/transcript or genes/transcripts of interest.

Hybridization assays based on polynucleotide arrays rely on the differences in hybridization stability of the probes to perfectly matched and mismatched target sequence variants. For SNP genotyping, it is generally preferable that stringency conditions used in hybridization assays are high enough such that nucleic acid molecules that differ from one another at as little as a single SNP position can be differentiated (e.g., typical SNP hybridization assays are designed so that hybridization will occur only if one particular nucleotide is present at a SNP position, but will not occur if an alternative nucleotide is present at that SNP position). Such high stringency conditions may be preferable when using, for example, nucleic acid arrays of allele-specific probes for SNP detection. Such high stringency conditions are described in the preceding section, and are well known to those skilled in the art.

In other embodiments, the arrays are used in conjunction with chemiluminescent detection technology.

In one embodiment of the invention, a nucleic acid array can comprise an array of probes of about 15-25 nucleotides in length. In further embodiments, a nucleic acid array can comprise any number of probes, in which at least one probe is capable of detecting one or more SNVs disclosed in Tables 1-3 and/or at least one probe comprises a fragment of one of the sequences selected from the group consisting of those disclosed herein, and sequences complementary thereto, said fragment comprising at least about 8 consecutive nucleotides, preferably 10, 12, 15, 16, 18, 20, more preferably 22, 25, 30, 40, 47, 50, 55, 60, 65, 70, 80, 90, 100, or more consecutive nucleotides (or any other number in-between) and containing (or being complementary to) a SNP. In some embodiments, the nucleotide complementary to the SNP site is within 5, 4, 3, 2, or 1 nucleotide(s) from the center of the probe, more preferably at the center of said probe.

A polynucleotide probe can be synthesized on the surface of the substrate by using a chemical coupling procedure and an ink jet application apparatus, as described in PCT application WO95/251116 (Baldeschweiler et al.) which is incorporated herein in its entirety by reference. In another aspect, a "gridded" array analogous to a dot (or slot) blot may be used to arrange and link cDNA fragments or oligonucleotides to the surface of a substrate using a vacuum system, thermal, UV, mechanical or chemical bonding procedures. An array, such as those described above, may be produced by hand or by using available devices (slot blot or dot blot apparatus), materials (any suitable solid support), and machines (including robotic instruments), and may contain 8, 24, 96, 384, 1536, 6144 or more polynucleotides, or any other number which lends itself to the efficient use of commercially available instrumentation.

The uses of the kits according to the invention typically involve incubating a test sample of nucleic acids with an array comprising one or more probes corresponding to at least one SNV position of the present invention, and assaying for binding of a nucleic acid from the test sample with one or more of the probes. Conditions for incubating a SNP detection reagent (or a kit/system that employs one or more of such SNP detection reagents) with a test sample vary. Incubation conditions depend on such factors as the format employed in the assay, the detection methods employed, and the type and nature of the detection reagents used in the assay. One skilled in the art will recognize that any one of the commonly available hybridization, amplification and array assay formats can readily be adapted to detect the SNPs disclosed herein.

A SNP detection kit/system of the present invention may include components that are used to prepare nucleic acids from a test sample for the subsequent amplification and/or detection of a SNP-containing nucleic acid molecule. Such sample preparation components can be used to produce nucleic acid, including DNA and/or RNA, extracts from any bodily fluids. In a preferred embodiment of the invention, the bodily fluid is blood, saliva or buccal swabs. The test samples used in the above-described methods will vary based on such factors as the assay format, nature of the detection method, and the specific tissues, cells or extracts used as the test sample to be assayed. Methods of preparing nucleic acids are well known in the art and can be readily adapted to obtain a sample that is compatible with the system utilized.

In yet another form of the kit, in addition to reagents for preparation of nucleic acids and reagents for detection of one of the SNVs of this invention, the kit may include measurements or a questionnaire inquiring about non-genetic clinical factors such as known to be associated with COVID-19 such as age, sex, smoking status, diabetes, hypertension, total cholesterol, high density lipoprotein (HDL)-cholesterol level, body mass index, pre-existing cardiovascular (CV) risk factors, such as male sex, chronic kidney disease, systolic blood pressure, diastolic blood pressure, glycaemia, high density lipoprotein, low density lipoprotein (LDL)- cholesterol level, triglycerides, glomerular filtration rate, renal insufficiency, left ventricular hypertrophy, alcohol consumption history, smoking history, exercise history, diet, family history of cardiovascular disease or disorder, coronary artery disease risk, history of heart failure, history of coronary artery disease, history of stroke, history of thrombosis, history of neoplasia, history of immune disease, history of COPD, history of mental/cognitive illness, and overt CV disease.

Another form of kit contemplated by the present invention is a compartmentalized kit. A compartmentalized kit includes any kit in which reagents are contained in separate containers. Such containers include, for example, small glass containers, plastic containers, strips of plastic, glass or paper, or arraying material such as silica. Such containers allow the user to efficiently transfer reagents from one compartment to another compartment such that the test samples and reagents are not cross-contaminated, or from one container to another vessel not included in the kit, and the agents or solutions of each container can be added in a quantitative fashion from one compartment to another or to another vessel. Such containers may include, for example, one or more containers which will accept the test sample, one or more containers which contain at least one probe or other SNP detection reagent for detecting one or more SNVs of the present invention, one or more containers which contain wash reagents (such as phosphate buffered saline, Tris-buffers, etc.), and one or more containers which contain the reagents used to reveal the presence of the bound probe or other SNP detection reagents. The kit can optionally further comprise compartments and/or reagents for, for example, nucleic acid amplification or other enzymatic reactions such as primer extension reactions, hybridization, ligation, electrophoresis (preferably capillary electrophoresis), mass spectrometry, and/or laser-induced fluorescent detection. The kit may also include instructions for using the kit. Exemplary 5 compartmentalized kits include micro fluidic devices known in the art (see, e.g., Weigl et al., "Lab-on-a-chip for drug development", Adv Drug Deliv Rev. 2003 Feb. 24;55(3):349-77). In such microfluidic devices, the containers may be referred to as, for example, microfluidic "compartments", "chambers", or "channels".

Microfluidic devices, which may also be referred to as "lab-on-a-chip" systems, biomedical micro-electro- mechanical systems (bioMEMs), or multicomponent integrated systems, are exemplary kits/systems of the present invention for analyzing SNVs. Such systems miniaturize and compartmentalize processes such as probe/target hybridization, nucleic acid amplification, and capillary electrophoresis reactions in a single functional device. Such microfluidic devices typically utilize detection reagents in at least one aspect of the system, and such detection reagents may be used to detect one or more SNVs of the present invention. One example of a microfluidic system is disclosed in U.S. Pat. No. 5,589,136, which describes the integration of PCR amplification and capillary electrophoresis in chips. Exemplary microfluidic systems comprise a pattern of microchannels designed onto a glass, silicon, quartz, or plastic wafer included on a microchip. The movements of the samples may be controlled by electric, electroosmotic or hydrostatic forces applied across different areas of the microchip to create functional microscopic valves and pumps with no moving parts. Varying the voltage can be used as a means to control the liquid flow at intersections between the micromachined channels and to change the liquid flow rate for pumping across different sections of the microchip. See, for example, U.S. Pat. No. 6,153,073, Dubrow et al, and U.S. Pat. No. 6,156,181, Parce et al.

For genotyping SNPs, a microfluidic system may integrate, for example, nucleic acid amplification, primer extension, capillary electrophoresis, and a detection method such as laser induced fluorescence detection.

In a third aspect, the means as defined for the second aspect form part of a kit. All means described above for the second aspect also apply to the kit of the third aspect.

In a fourth aspect, the invention refers to use of means as defined in the second aspect or a kit as defined in the third aspect for predicting the risk of a subject of developing severe COVID-19 as defined in the first aspect. All embodiments described for the first, second and third aspects, including all means described above, are applicable to this fourth aspect.

In a fifth aspect, the invention refers to an in vitro method for deciding or recommending a medical regime to a subject, said method comprising: (i) predicting the risk of a subject to develop severe COVID-19 as defined in the first aspect, and (ii) recommending or deciding a medical regime if the subject is predicted to have a high risk of developing severe COVID-19.

In one embodiment of the fifth aspect, the method comprises a medical regime, which is adequate for the treatment of any condition associated to severe COVID-19. In a particular embodiment, the medical regime is selected from the high-risk group consisting of monitoring, and usual severe COVID-19 care including but not limited to hospitalization, oxygen supplementation treatment, administering antithrombotic agents, administering antibiotics, antiviral drugs, administering anti-inflammatory agents, and combinations thereof.

The sixth aspect of the invention is the combined use of the following SNVs: rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637 (SNVs from table 1), and, optionally, of one or more further SNVs selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714 (SNVs of table 2), and combinations thereof, as a genetic marker for predicting the risk of a subject to develop severe COVID-19.

A particular embodiment of the sixth aspect provides for the combined use of the SNVs of table 1 and at least two further SNVs from table 2. A particular embodiment provides for the combined use of the SNVs of table 1 and at least three further SNVs from table 2. A particular embodiment provides for the combined use of the SNVs of table 1 and at least four further SNVs from table 2. A particular embodiment provides for the combined use of the SNVs of table 1 and the five further SNVs from table 2.

An additional aspect of the invention refers to an in vitro method for identifying a patient in need of early and/or aggressive therapy for COVID-19 or in need of prophylactic therapy comprising:(i) predicting the risk of a subject to develop severe COVID-19 as defined in the first aspect, (ii) identifying that the subject is in need of early and/or aggressive therapy for COVID-19 or in need of prophylactic therapy when a high risk of severe COVID-19 is determined. In one embodiment, early therapy may include but is not limited to hospitalization, oxygen supplementation treatment, administering antithrombotic agents, administering antibiotics, antiviral drugs, administering anti-inflammatory agents, and combinations thereof. In one embodiment, aggressive therapy comprises the above and admission to intensive care unit, intubation for respiratory assistance, extracorporeal membrane oxygenation and other necessary treatments. In one embodiment, prophylactic therapy comprises but is not limited to full vaccination, isolation, and antiviral drugs.

The method of the invention may be automated in order to provide a risk prediction or prognostic result. Thus, the invention also provides a system for determining the risk to develop severe COVID-19 in a patient comprising data processing means, said data processing means been configured: - to assess in a test sample obtained from the patient the presence or absence of risk alleles at the following SNVs: rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, and, optionally, further risk alleles at SNVs selected from rs1801020, rs4961252, rs2246833, rs4830974, rs75885714, rs5936011 , rs6632704, rs2158082, rs6629110, and combinations thereof, and/or other non-genetic risk factors as defined above, and

- to determine the risk of developing severe COVID-19 by evaluating the result of the previous assessed parameters, for example by applying an algorithm.

The in vitro method of the invention generally provides for determining the risk to develop severe COVID-19 in a patient and for recommending an appropriate medical regime for the treatment of said patient. In some embodiments, said method may further comprise the steps of (I) collecting the risk prediction information, and (II) saving the information in a data carrier.

In the sense of the invention a "data carrier” is to be understood as any means that contain meaningful information data for determining the risk to develop severe COVID-19 in a patient and/or recommending an appropriate medical regime, such as paper. The carrier may also be any entity or device capable of carrying the prognosis data or information for recommending an appropriate therapy. For example, the carrier may comprise a storage medium, such as a ROM, for example a CD ROM or a semiconductor ROM, or a magnetic recording medium, for example a floppy disc or hard disk. Further, the carrier may be a transmissible carrier such as an electrical or optical signal, which may be conveyed via electrical or optical cable or by radio or other means. When the risk prediction data are embodied in a signal that may be conveyed directly by a cable or other device or means, the carrier may be constituted by such cable or other device or means. Other carriers relate to USB devices and computer archives. Examples of suitable data carrier are paper, CDs, USB, computer archives in PCs, or sound registration with the same information.

For completeness, the present description is also disclosed in the following numbered embodiments:

1 . An in vitro method for predicting the risk of a subject to develop severe coronavirus disease 2019 (COVID- 19), said method comprising the step of determining, in a sample isolated from the subject, the presence or absence of risk alleles at the following single nucleotide polymorphisms (SNPs): rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637.

2. An in vitro method according to embodiment 1, wherein the presence or absence of at least one risk allele is indicative of an increased risk of developing severe COVID-19.

3. The in vitro method according to any of the preceding embodiments, wherein the risk alleles are those disclosed in Table 1.

4. The method according to any one of the preceding embodiments, further comprising determining the presence or absence of risk alleles at a SNP selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714, and combinations thereof.

5. The in vitro method according to the preceding embodiment, wherein at least rs1801020 is determined.

6. The in vitro method according to any of embodiments 4-5, wherein at least rs4961252 is determined. 7. The in vitro method according to any of embodiments 4-6, wherein at least rs4830974 is determined.

8. The in vitro method according to any of embodiments 4-7, wherein at least rs2246833 is determined.

9. The in vitro method according to any of embodiments 4-8, wherein at least rs75885714 is determined.

10. The in vitro method according to any of embodiments 4-9, wherein the risk alleles at the SNPs selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714 are those disclosed in table 2.

11 . The in vitro method according to any one of the preceding embodiments, wherein the presence of at least two risk alleles is indicative of an increased risk of developing severe COVID-19.

12. The in vitro method according to any of the preceding embodiments, wherein the presence of at least three risk alleles is indicative of an increased risk of developing severe COVID-19.

13. The in vitro method according to any of the preceding embodiments, wherein the presence of at least four risk alleles is indicative of an increased risk of developing severe COVID-19.

14. The in vitro method according to any of the preceding embodiments, wherein the presence of at least five risk alleles is indicative of an increased risk of developing severe COVID-19.

15. The in vitro method according to any of the preceding embodiments, wherein the presence of at least six risk alleles is indicative of an increased risk of developing severe COVID-19.

16. The in vitro method according to any of the preceding embodiments, wherein the presence of at least seven risk alleles is indicative of an increased risk of developing severe COVID-19.

17. The in vitro method according to any of the preceding embodiments, wherein the presence of at least eight risk alleles is indicative of an increased risk of developing severe COVID-19.

18. The in vitro method according to any of the preceding embodiments, wherein the presence of at least nine risk alleles is indicative of an increased risk of developing severe COVID-19.

19. The in vitro method according to any of the preceding embodiments, wherein the presence of at least ten risk alleles is indicative of an increased risk of developing severe COVID-19.

20. The in vitro method according to any of the preceding embodiments, wherein the presence of a risk allele in at least rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, is indicative of an increased risk of developing severe COVID-19.

21. The in vitro method according to any of the preceding embodiments, wherein the presence of a risk allele in at least rs11385942, rs12190287, rs1746048, rs13109457, rs17465637, rs1801020, rs4961252, rs4830974, rs2246833 and rs75885714, is indicative of an increased risk of developing severe COVID-19.

22. The in vitro method according to any of the preceding embodiments, wherein the severe COVID-19 comprises a complication selected from the group consisting of respiratory frequency >30 times/min, a blood oxygen saturation <93%, presence of infiltrates in >50% of pulmonary fields within 24 to 48 hours of symptom onset, pneumonia, required mechanical ventilation, cardiovascular complications, thrombotic complications, hyperinflammatory syndrome, death, and combinations thereof.

23. The in vitro method according to any of the preceding embodiments, wherein the sample obtained from the subject is a tissue or a bodily fluid.

24. The in vitro method according to the preceding embodiment, wherein the sample is selected from blood, plasma, serum, oral tissue, oral scraping, oral wash, saliva, sweat or urine. 25. The in vitro method according to any of the preceding embodiments, wherein the sample is blood or saliva.

26. The in vitro method according to any of the preceding embodiments, wherein determining the presence or absence of the risk comprises hybridization of a nucleotide probe.

27. The in vitro method according to the preceding embodiment, wherein the probe contains a detectable label.

28. The in vitro method according to any one of embodiments 26-27, further comprising a step of amplifying the region where the SNP is located.

29. The in vitro method according to any of the preceding embodiments, wherein determining the presence or absence of the risk alleles comprises genotyping.

30. The in vitro method according to the preceding embodiment, wherein the method comprises the determination of the presence or absence of the risk alleles which is carried out by a method comprising the following steps:

- Genomic DNA extraction from the samples using an adequate method;

- Optionally, a pre-amplification;

- Genotyping of DNA samples using an adequate genotyping technology such as the TaqMan® SNP following manufacturer's instructions;

- Fluorescence data collection with proper readers, such as Fluidigm EP1 Reader; which at the end of the PGR reaction, the fluorescent signal for the two reporter dyes is measured. The ratio of the signals will be indicative for the genotype of the sample; and

- Data analysis to obtain genotype calls using adequate software, such as Fluidigm SNV Genotyping Analysis Software.

31. The method according to any one of the preceding embodiments, wherein subjects are aged between 35 and 85 years.

32. The method according to any one of the preceding embodiments, wherein subjects are aged between 35 and 45 years.

33. The method according to any one of the preceding embodiments, further comprising computing a Genetic Risk Score (GRS).

34. The method according to the preceding embodiment, wherein the GRS is computed as the unweighted count (0, 1 or 2) of risk alleles of the independent SNPs, and in men, SNPs on the X chromosome are counted as 0 or 2.

35. The method according to any one of the embodiments 33-34, further comprising calculating a risk probability to develop sever COVID-19 by multiplying the GRS of a subject by a genetic risk regression coefficient.

36. The method according to the preceding embodiment, wherein for a method in which rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637 are the determined SNVs, the genetic risk regression coefficient is 0.058.

37. The method according to the embodiment 35, wherein for a method in which rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637 are the determined SNVs and the subject is aged 35 to 45 years, the genetic risk regression coefficient is 0.07696.

38. The method according to the embodiment 35, wherein for a method in which rs11385942, rs12190287, rs1746048, rs13109457, rs17465637, rs11385942, rs12190287, rs1746048, rs13109457, rs17465637, rs1801020, rs4961252, rs4830974, rs2246833, and rs75885714 are the determined SNVs, the genetic risk regression coefficient is 0.03922.

39. The method according to the embodiment 35, wherein for a method in which rs11385942, rs12190287, rs1746048, rs13109457, rs17465637, rs11385942, rs12190287, rs1746048, rs13109457, rs17465637, rs1801020, rs4961252, rs4830974, rs2246833, and rs75885714 are the determined SNVs, and the subject is aged 35 to 45 years, the genetic risk regression coefficient is 0.05826.

40. The method according to any one of the embodiments 33-39, wherein the risk probability to develop severe COVID-19 can be adjusted with other constants.

41. The method according to any of the preceding embodiments, further comprising determining other genetic markers, biomarkers and/or any other risk factor associated to COVID-19 severity may be used to improve the risk prediction.

42. The method according to any of the preceding embodiments, further comprising determining additional non-genetic risk factors from the subject selected from the group of age, sex, smoking status, diabetes, hypertension, total cholesterol, high density lipoprotein (HDL)-cholesterol level, body mass index, pre-existing cardiovascular (CV) risk factors, such as male sex, chronic kidney disease, systolic blood pressure, diastolic blood pressure, glycaemia, high density lipoprotein, low density lipoprotein (LDL)-cholesterol level, triglycerides, glomerular filtration rate, renal insufficiency, left ventricular hypertrophy, alcohol consumption history, smoking history, exercise history, diet, family history of cardiovascular disease or disorder, coronary artery disease risk, history of heart failure, history of coronary artery disease, history of stroke, history of thrombosis, history of neoplasia, history of immune disease, history of COPD, history of mental/cognitive illness, and overt CV disease, and combinations thereof.

43. The method according to the preceding embodiment, wherein non-genetic risk factors are selected from the group of age, sex, smoking status, diabetes, hypertension, total cholesterol, high density lipoprotein (HDL)-cholesterol level, body mass index.

44. The method according to any of the preceding embodiments, further comprising computing a model for determining the risk of a subject to develop severe COVID-19 considering the GRS and additional non-genetic risk factors.

45. The method according to the preceding embodiment, wherein the risk probability to develop severe COVID-19 is computed using the formula:

Log (risk odds) = (GRS*genetic risk regression coefficient) + E(non-genetic risk factor*non-genetic risk factor regression coefficient)

46. The method according to the any of the embodiments 44-45, wherein the GRS is computed with the 5 SNPs of table 1 and the coefficients are those defined in table 5.

47. The method according to any of the preceding embodiments, further comprising computing an algorithm based on the GRS and additional non-genetic risk factors according to their coefficients and optionally applying further adjustments and/or constants. 48. The method according to any of the preceding claims, further comprising communicating the result.

49. Means for detecting the presence or absence of risk alleles at the following single nucleotide polymorphisms (SNPs): rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637.

50. Means according to the preceding embodiment, wherein the risk alleles are those disclosed in Table 1.

51. Means according to the preceding embodiment, further comprising means for detecting the presence or absence of risk alleles at a SNP selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714, and combinations thereof.

52. Means according to the preceding embodiment, wherein the risk alleles are those disclosed in Table 1 and Table 2.

53. Means according to any one of embodiments 49-52, wherein the means comprise nucleic acid probes which stringently hybridize with the risk alleles, in particular probes that contain a detectable label.

54. Means according to any one of embodiments 49-53, wherein the means comprise an array, in particular a microarray.

55. A kit comprising means as defined in any one of embodiments 49-54.

56. The kit according to the preceding embodiment further comprising instructions for predicting the risk of a subject to develop severe COVID-19 as defined in any one of embodiments 1-48.

57. Use of means as defined in any one of embodiments 49-54 or of a kit as defined in any one of embodiments 55-56, for predicting the risk of a subject of developing severe COVID-19 as defined in any one of embodiments 1-48.

58. An in vitro method for deciding or recommending a medical regime to a subject, said method comprising: (I) predicting the risk of a subject to develop severe COVID-19 as defined in any one of embodiments 1-48, and

(ii) recommending or deciding a medical regime if the subject is predicted to have a high risk of developing severe COVID-19.

59. The method according to the preceding embodiment, wherein the medical regime is adequate for the treatment of any condition associated to severe COVID-19.

60. The method according to the preceding embodiment, wherein the medical regime is selected from the group consisting of vaccination, isolation, hospitalization, oxygen supplementation, administering antithrombotic agents, administering antibiotics, administering antiviral drugs, administering anti-inflammatory agents, admission to intensive care unit, intubation for respiratory assistance, extracorporeal membrane oxygenation, and combinations thereof.

61. Combined use of the following SNVs: rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, as a genetic marker for predicting the risk of a subject to develop severe COVID-19.

62. The combined use according to the preceding embodiment, further comprising the combined use of one or more of the SNPs selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714 (SNPs of table 2), and combinations thereof.

63. The combined use according to the preceding embodiment, wherein at least rs4961252 is used.

64. The combined use according to any one of embodiments 62-63, wherein at least rs4830974 is used.

65. The combined use according to any one of embodiments 62-64, wherein at least rs2246833 is used. 66. The combined use according to any one of embodiments 62-65, wherein at least rs75885714 is used.

67. The combined use according to any one of embodiments 62-65, wherein at least rs1801020 is used.

68. An in vitro method for identifying a patient in need of early and/or aggressive therapy for COVID-19 or in need of prophylactic therapy comprising:

(I) predicting the risk of a subject to develop severe COVID-19 as defined in embodiments 1-48, and (ii) identifying that the subject is in need of early and/or aggressive therapy for COVID-19 or in need of prophylactic therapy when a high risk of severe COVID-19 is determined.

69. The method according to the preceding embodiment, wherein early therapy is selected from the group of hospitalization, oxygen supplementation, administering antithrombotic agents, administering antibiotics, administering antiviral drugs, administering anti-inflammatory agents, and combinations thereof.

70. The method according to embodiment 68, wherein aggressive therapy comprises admission to intensive care unit, intubation for respiratory assistance, extracorporeal membrane oxygenation, or combinations thereof.

71. The method according to embodiment 68, wherein prophylactic therapy comprises vaccination, isolation, administering antiviral drugs, or combinations thereof.

Throughout the description and claims the word "comprise" and variations of the word, are not intended to exclude other technical features, additives, components, or steps. Furthermore, the word "comprise” encompasses the case of "consisting of'. Additional objects, advantages and features of the invention will become apparent to those skilled in the art upon examination of the description or may be learned by practice of the invention. The following examples are provided by way of illustration, and they are not intended to be limiting of the present invention. Furthermore, the present invention covers all possible combinations of particular and preferred embodiments described herein.

Examples

1. Study design and participants

An age (±10 years)- and sex-matched case-control study with a 1 :2 recruitment ratio was carried out in Catalonia, north-eastern Spain. 3,314 patients aged 35 to 85 years were recruited. Participants had tested positive for SARS-CoV-2 (RT-PCR, rapid antigen, or IgG test results) between February 2020 and June 2021. Cases were consecutively hospitalized patients receiving oxygen treatment due to respiratory frequency >30 times/min, blood oxygen saturation <93%, or to infiltrates in >50% of pulmonary fields. Controls were patients with mild or no symptoms, treated at home and not requiring oxygen therapy. Participants were excluded if no clinical data were available in the electronic medical record of the Catalan health system (universal coverage) or if they were vaccinated against COVID-19 before the diagnosis.

Cases' blood samples were obtained as soon as possible during hospitalization. Controls were directed to an outpatient clinic, where trained nurses performed the examinations and collected blood or saliva samples to extract DNA.

Data on age, sex, height, weight, and blood pressure were collected during admission (cases) or at the outpatient clinic (controls). Clinical data prior to the COVID-19 infection were collected from electronic medical records including history of smoking, arterial hypertension, dyslipidaemia, diabetes, CAD, stroke, thromboembolism, and chronic obstructive pulmonary disease (COPD). The most recent glycemia, lipid profile, and creatinine values were also obtained from electronic medical records.

Results 3,314 candidate COVID-19 patients aged 35 to 85 years were recruited. After excluding those who did not met inclusion criteria (n=188), and performing age- and sex-matching, 2,454 patients (818 cases and 1,636 controls) were retained in the analysis. Table 6 shows the prevalence of risk factors and clinical characteristics in matched and non-matched patients. Table 6. Risk factors and clinical characteristics prevalence

* Mean (standard deviation). COPD, chronic obstructive pulmonary disease; HDL, high-density lipoprotein; IQR, Inter-Quartile Range; LDL, low-density lipoprotein.

Demographic, anthropometric, and clinical characteristics of cases and controls are shown in Table 7. Cases had significantly higher prevalence of diabetes and hypertension, and more often previous stroke, thrombosis, neoplasia, and COPD. Levels of systolic blood pressure, glycaemia, triglycerides, body mass index, and CAD risk were also higher in cases. Although cases and controls had a low smoking prevalence, cases had a significantly lower proportion of smokers than controls. Cases also had lower diastolic blood pressure and HDL cholesterol levels. Table 7. Demographic, anthropometric, and clinical characteristics of matched cases and controls

* Mean (standard deviation). COPD, chronic obstructive pulmonary disease; HDL, high-density lipoprotein;

IQR, Inter-Quartile Range; LDL, low-density lipoprotein.

2. Single Nucleotide Variants & Genetic Risk Scores

Genomic DNA Extraction

Genomic DNA from each patient was extracted from peripheral venous blood collected in 4 mL EDTA AntiCoagulant BD Vacutainer tubes or saliva collected in DANASALIVA Sample Collection kit (DANAGEN)-. The Hospital del Mar Medical Research Institute (IMIM) laboratory performed the DNA extraction of the blood samples from Hospital del Mar and Hospital Universitari de Vic under strict biohazard prevention regulations. The samples collected were frozen at -80°C without centrifugation until DNA extraction. DNA was isolated from whole blood by liquid-liquid extraction (FlexiGene DNA Kit, Qiagen). Lysis buffer was added and cell nucleus and mitochondria were pelleted by centrifugation. The pellet was resuspended and incubated in denaturation buffer, which contained a chaotropic salt and QIAGEN Protease. This step efficiently removed contaminants such as proteins. DNA was precipitated by addition of isopropanol, recovered by centrifugation, washed in 70% ethanol, dried, and finally resuspended in hydration buffer (10 mM Tris.CI, pH 8.5). The Girona Biomedical Research Institute (IDIBGI) performed the genomic DNA extraction of samples from Hospital Universitari Dr. Josep Trueta and IDIAPJGol. They used the ChemagicTM DNA Blood 7k Kit H12 (PerkingElmer) on a Chemagic MSM I instrument regardless of sample origin. Resulting DNA was eluted in 300pL of Elution Buffer (PerkinElmer), quality-checked on a Nanodrop ND-1000 Spectrophotometer (Thermo Scientific), and stored at -20°C until used.

DNA quality and quantity needed for the genotyping analysis met the following requirements: >=60ng/ul (minimum amount =500ng) and 260/280 ratio between 1.8 and 2.0.

Single Nucleotide Variants Genotyping

Genomic DNA was extracted from peripheral blood collected in 4-mL EDTA Anti-Coagulant BD Vacutainer tubes or from saliva collected in DANASALIVA Sample Collection kit (DANAGEN). DNA extraction was performed using a ChemagicTM DNA Blood 7k Kit H12 (PerkingElmer) on a Chemagic MSM I instrument or a FlexiGene DNA Kit (Qiagen).

DNA samples were genotyped by TaqMan Open Array Technology as follows.

Prior to SNV genotyping on the Fluidigm Nanofluidic 96*96 dynamic array, genomic DNA samples were normalized to 60 ± 5 ng/pl and subjected to pre-amplification. For each sample, a 5 pl sample mix (2.5 pl of 2X Multiplex Master mix (QIAGEN), 1.25 pl of previously pooled SNP-genotyping probes, and 1.25 pl of normalized genomic DNA) was prepared and incubated on a thermal cycler under the following conditions: 15 minutes at 95°C; 14 cycles of 15 seconds at 95°C and 4 minutes at 60°C; and hold at 12°C.

After pre-amplification, 5 pl of sample loading mixes (3 pl of 2X GTXpress Master Mix, 0.3 pl of 20X Fast GT sample loading reagent, 0.2 pl of PCR-certified water, and 2.5 pl of pre-amplified DNA diluted % in TE 1 X) and 4 pl of genotyping assay mixes (2.5 pl of 2X Assay loading reagent, 0.25 pl of ROX reference dye 50X, and 1 pl of PCR-certified water) were loaded into the corresponding sample and assay chip inlets from the 96*96 dynamic array. Prior to loading sample and assay mixes into the inlets, the chip was primed in the Fluidigm IFC Controller HX. Once loaded, the chip was placed on the Fluidigm IFC Controller HX for loading and mixing. After loading, the chip was placed on a FC1 Cycler for PCR amplification under the following conditions: 30 minutes at 70°C; 10 minutes at 25°C; 2 minutes at 95°C; 45 cycles of 2 seconds at 95°C and 20 seconds at 60°C; hold at 25°C. Fluorescence data was collected on the Fluidigm EP1 Reader and data was analyzed using Fluidigm SNP Genotyping Analysis Software to obtain genotype calls. Each 96*96 dynamic array was loaded with 88 samples, 6 positive controls (HG01762, HG01060, HG00641, HG01847, HG01440 and NA20531), and 2 negative controls to validate the match between obtained and expected genotypes.

For SNV genotyping on the Fluidigm Nanofluidic 96*96 dynamic array, 90 samples + 4 positive controls + 2 negative controls were genotyped.

The SNVs of table 1, table 2 and table 3 were selected and genetic risk scores (GRSs) were computed as the unweighted count of the risk alleles (0, 1 or 2) of the independent SNVs. Risk alleles are also disclosed in table 1, table 2 and table 3. In men, SNVs on the X chromosome were coded only as 0 or 2. Two GRS models were tested, one with all significant and independent SNVs (the 10 SNVs of table 1 and table 2), and another with the minimum number of SNVs (the 5 SNVs of table 1) needed to produce a similar improvement in discriminating COVID-19 severity.

Results

Genetic risk scores

In the GRS that included the selected 10 significant and independent SNVs of table 1 and table 2, the median number of risk alleles was 7 in cases and 6 in controls (Figure 2). With the 10-SNVs GRS, the odds of COVID-19 severity increased by 9% (95%CI : 7-12) per standard deviation of the GRS, and by 4% per risk allele (95%CI:3-5%) (Table 5). The discrimination, as measured by AUG, was 4 percentual units higher and continuous net reclassification index (NRI) was 26 (95%CI: 16-35) with GRS added to a basic clinical model with age, diabetes, hypertension, BMI, lipid profile, and smoking (Table 5).

The smallest subset of SNVs that yielded similar discrimination performance as the 10-SNV model turned out to be of 5 SNVs (those defined in table 1). The median number of risk alleles was 4 in cases and 3 in controls (Figure 1).

In the 5-SNV GRS, the odds of severe COVID-19 increased by 8% (95% Cl 6-10) per standard deviation of the GRS, and by 6% per risk allele (95% Cl: 4-7%). The 5-SNVs GRS improved the AUG (3%) and continuous NRI by 33 (95%CI: 24-43) of the basic model (Table 5). In other words, the GRS most associated with severity and with the lowest number of SNVs (rs12190287, rs1746048, rs17465637, rs13109457 and rs11385942) yielded an adjusted GR=1.06 (95%CI: 1.04-1.07) per risk allele and an AUC=0.73 (95%CI: 0.70- 0.75). This GRS significantly improved continuous net reclassification index (33% (95%CI: 24-43)) of a model with risk factors alone.

The association of both GRSs with severe COVID-19 differed by age (p-value of the interaction term <0.001), showing a decreasing effect with ageing.

With the 10-SNVs GRS the odds of severe COVID-19 was 6% (95% Cl 5-8) per risk allele in a 40-year-old patient, and 2% (95% Cl 1-4) in an 80-year-old patient.

With the 5-SNVs GRS it was 8% (95% Cl 5-11) and 3% (95% Cl 1-6), respectively. In other words, the 5- SNVs GRS yielded an adjusted CR=1.08 (95%CI: 1.04-1.12) in patients aged 35- 45 years.

Citation List

Patent Literature

U.S. Pat. No. 6159693

U.S. Pat. No. 4883750

U.S. Pat. No. 5837832

PCT application WO95/11995 (Chee et al.)

U.S. Patent Application No. 10/620332

U.S. Patent application No. 10/620333

U.S. Pat. No. 6124478

U.S. Pat. No. 6107024

U.S. Pat. No. 5994073

U.S. Pat. No. 5981768

U.S. Pat. No. 5871938

U.S. Pat. No. 5843681

U.S. Pat. No. 5800999

U.S. Pat. No. 5773628

U.S. Patent Application No. 10/050188

PCT application WO95/251116 (Baldeschweiler et al.)

U.S. Pat. No. 5589136

U.S. Pat. No. 6153073

U.S. Pat. No. 6156181

U.S. Pat. No. 5807522

Non Patent Literature

Lockhart, D. J. et al. (1996; Nat. Biotech. 14: 1675- 1680)

Schena, M. et al. (1996; Proc. Natl. Acad. Sci. 93: 10614-10619)

Zammatteo et al., "New chips for molecular biology and diagnostics", Biotechnol Annu Rev. 2002;8:85-101

Sosnowski et al., "Active microelectronic array system for DNA hybridization, genotyping and pharmacogenomic applications", Psychiatr Genet. 2002 December; 12(4): 181-92

Heller, "DNA microarray technology: devices, systems, and applications", Annu Rev Biomed Eng. 2002;4: 129-53. Epub 2002 Mar 22

Kolchinsky et al., "Analysis of SNPs and other genomic variations using gel- based chips", Hum Mutat. 2002

April; 19(4):343-60

McGall et al., "High- density genechip oligonucleotide probe arrays", Adv Biochem Eng Biotechnol. 2002:77:21-42

Weigl et al., "Lab-on-a-chip for drug development", Adv Drug Deliv Rev. 2003 Feb. 24;55(3):349-77

Claims

1 . An in vitro method for predicting the risk of a subject to develop severe coronavirus disease 2019 (COVID-19), said method comprising the step of determining, in a sample isolated from the subject, the presence or absence of risk alleles at the following single nucleotide variants (SNVs): rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, and wherein the risk alleles are those disclosed in Table 1, and wherein the presence of at least one risk allele is indicative of an increased risk of developing severe COVID-19.

2. The in vitro method according to the preceding claim, wherein the presence of at least two, at least three, at least four, or at least five risk alleles is indicative of increased risk of developing severe COVID- 19.

3. The method according to any of the preceding claims, further comprising communicating the result.

4. The method according to any one of the preceding claims, further comprising determining the presence or absence of risk alleles at a SNV selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714, and combinations thereof, wherein the risk alleles are those disclosed in Table 2.

5. The method according to any one of the preceding claims, said method comprising determining the presence or absence of risk alleles at each of the following single nucleotide variants (SNVs): rs11385942, rs12190287, rs1746048, rs13109457, rs17465637, rs1801020, rs4961252, rs4830974, rs2246833, and rs75885714, wherein the presence of at least one risk allele for each of the SNVs is indicative of an increased risk of developing severe COVID-19.

6. The method according to any one of the preceding claims, wherein the sample is a bodily fluid or tissue.

7. The method according to any one of the preceding claims, wherein subjects are aged between 35 and 45 years

8. The method according to any of the preceding claims, wherein determining the presence or absence of the risk alleles comprises hybridizing with a nucleotide probe.

9. The method according to any one of the preceding claims, further comprising determining a risk factor selected from the group consisting of age, sex, smoking status, diabetes, hypertension, total cholesterol, high density lipoprotein (HDL)-cholesterol level, body mass index, and combinations thereof.

10. A kit comprising means for detecting the presence or absence of risk alleles at the following single nucleotide variants (SNVs): rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, wherein the risk alleles are those disclosed in Table 1.

11 . The kit according to the preceding claim, wherein the means comprise nucleic acid probes which stringently hybridize with the risk alleles.

12. An in vitro method for deciding or recommending a medical regime to a subject, said method comprising:

(I) predicting the risk of a subject to develop severe COVID-19 as defined in any one of claims 1-9, and

13. The method according to the preceding claim, wherein the medical regime is selected from the group consisting of vaccination, isolation, hospitalization, oxygen supplementation, administering antithrombotic agents, administering antibiotics, administering antiviral drugs, administering anti-inflammatory agents, admission to intensive care unit, intubation for respiratory assistance, extracorporeal membrane oxygenation, and combinations thereof.

14. Combined in vitro use of the following SNVs: rs11385942, rs12190287, rs1746048, rs13109457, and rs17465637, and, optionally, of one or more further SNVs selected from the group consisting of rs1801020, rs4961252, rs4830974, rs2246833, rs75885714, and combinations thereof, as a genetic marker for predicting the risk of a subject to develop severe COVID-19.