Method for predicting risk of serious outcome upon becoming infected with a virus

Abstract

Disclosed herein is a method that uses genetic information of a subject collected by methods such as using a saliva or blood sample collection kit. In the method, genotype data obtained from a specific region of the DNA is extracted from the blood or saliva sample and interpreted using a set of algorithms and models disclosed herein to predict the risk that a subject will have a severe outcome such as hospitalization or death upon exposure to viral infection.

Description

[0001] METHOD FOR PREDICTING RISK OF SERIOUS OUTCOME UPON BECOMING INFECTED WITH A VIRUS

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 531,367, filed August 8, 2023, the contents of which are incorporated herein by reference in their entirety.

[0004] TECHNICAL FIELD

[0005] This disclosure pertains to genetic analysis of blood samples to predict the risk of severe or fatal outcome from a viral infection.

[0006] BACKGROUND

[0007] Interferon (IFN) plays an important role in first line of defense of human’s immune response to infections, including by aggressive viruses such as SARS-CoV-2, Hepatitis B / C, HIV, Influenza H1N1. When an individual is exposed to a viral infection the immune system responds by producing IFN. Importantly, the amount produced or rate of production significantly varies across individuals including within the same ancestral cohorts. This production rate of IFN plays a role in determining the strength of an individual’s immune response against viral infections, and can determine the difference between a mild, serious, or fatal infection outcomes.

[0008] The severity of a viral infection varies widely between individuals, and genetic factors play a role in this variability. Type I interferon (IFN) is an anti-viral cytokine, and differences in type I IFN levels exist between world populations. Despite therapeutic developments, viral infections continue to cause significant death tolls in the world. As the world witnessed in the recent COVID-19 pandemic, virus evolution and mutations can lead to outbreaks that have far-reaching consequences. Despite advances in vaccines and therapeutics, viral infections continue to cause significant morbidity and mortality throughout the world. Viruses remain a threat as their high mutation rate and ability to live within cells can outpace the human immune response and lead to outbreaks as the world witnessed in the recent COVID-19 pandemic, previous pandemics such as influenza H1N1, and other viral threats such as Ebola and HIV. The severity of a viral infection typically varies significantly between individuals, ranging from mild symptoms to severe organ failure and death, which may depend on a variety of factors including host genetics, comorbidity, socio-economics and demographics, and access to healthcare.

[0009] One of the main components in human immune defense against viral infection is type I IFN. When an individual is exposed to a viral infection, the immune system responds by producing type I IFN resulting in interferon-stimulated gene (ISG) induction. The innate immune cell’s pattern recognition receptors (PRR) are stimulated by foreign nucleic acids, resulting in JAK / STAT pathway signaling that leads to increased expression of innate immune genes, including interferon-stimulated genes. IFNs fight viral infection in a number of ways, including by inducing neighboring infected cells to undergo apoptosis to limit spread of the infection, and by upregulating antigen presentation and co-stimulatory molecule expression which activates adaptive immune cells. The transcription rate and regulation of IFN may significantly vary across individuals including within the same ancestral cohorts. These differences in type I IFN play a role in determining the strength of an individual’s immune response against viral infections, and can determine the difference between a mild, serious, or fatal infection outcome.

[0010] IFN has been known to play an important role in systemic lupus erythematosus (SLE) pathogenesis and have a significant genetic component in lupus patients, where certain alleles are correlated with increased type I IFN pathway activation and other alleles correlate with reduced type I IFN. Recently we observed an inverse correlation between these known genetic polymorphisms in their response to SARS-CoV-2 viral infection mortality rates, where high IFN risk alleles discovered in lupus patients correlated with lower COVID-19 mortality rates, while low IFN risk alleles correlated with higher COVID-19 mortality rates. The result also shows the importance of common genetic variations in the IFN pathway not just in lupus susceptibility, but also in modulating the severity of SARS-CoV-2 infection in the general population.

[0011] Given the role of IFN in determining the strength of an individual’s immune response against viral infections, and the severity of infection outcomes, there exists a need for methods of predicting, at the individual level, the risk of viral infection, including serious outcome or fatality, which can have a life-saving impact. Such methods would allow individuals that are predicted to be high-risk to take preventative actions such as stricter isolation, be assigned into a high-risk group to receive priority vaccines and / or boosters, medications, etc. Further, such methods would enhance public health control capabilities and facilitate policy implementation to deploy measures that can help limit the spread of viral infection outbreaks today and in the future.

[0012] SUMMARY

[0013] It has now been found genetics play an important role in determining the rate of IFN production or gene expression. Particular genetic variants can be statistically significantly correlated with the IFN response. Given the central role that IFN plays in a person’s immune response to viral infections, methods disclosed herein enable the prediction of severe or fatal viral infection risk at the individual level, by way of genetic testing that can be performed very early, using relatively standard processes of DNA collection such as saliva or blood sampling.

[0014] The methods disclosed herein provides a genetic test that enables an early detection, at the individual level, of the risk of viral infection, including serious outcome or fatality, which can have a life-saving impact. Individuals that are predicted to be at- risk may take preventative actions such as stricter isolation, be assigned into a high-risk group to receive priority vaccines and / or boosters, medications, etc. Further, the methods disclosed herein could also help with public health control and policy implementation to deploy measures that can help limit the spread of viral infection outbreaks today and in the future.

[0015] DNA collection kits can be produced at a relatively low cost and can be used at scale by many individuals during outbreaks or otherwise, to quickly gain insight on the individual’s risk of severe / fatal viral infection outcome. Individuals who are at-risk of severe viral infection can then take preventative actions such as stricter isolation from viral exposure, priority vaccines and / or boosters, medications, or close monitoring. With public health coordination, consolidation of the collective data could also be highly valuable and help with policy implementation and outbreak control at the community level.

[0016] The methods disclosed herein are based, at least in part, on the discovery of the interrelationship between regional European genetic ancestry, type I IFN levels, and risk of severe viral infection outcomes. Regional ancestry within Europe was determined using a validated set of European- American ancestry informative markers (AIMs). Principal component analysis was performed on the AIMs data to infer each subject’s proportional regional European ancestry. In cohorts of European ancestry lupus patients, we noted a Northwest vs. Southeast gradient in type I IFN levels. We then studied an independent cohort of lupus patients with varying proportional regional European genetic admixture where we observed a significant gradient in IFN level. Using these data, we developed a model to predict type I IFN level based on regional European ancestry. Using large European countries’ viral infection databases, we found that lower predicted IFN level in the corresponding European country was significantly correlated with increased fatality rate due to viral infections, including COVID-19, viral hepatitis, and HIV, (r = -0.79 (p = 4 x 1 O'2), -0.94 (p = 6 x 10'3) to -0.96 (p = 8 x 1 O'2)) respectively. This association is consistent with the expectation that greater intrinsic type I IFN response is beneficial in host defense against viral infection. These findings suggest that genetic testing could provide insight into an individual’s risk of fatality due to viruses prior to infection, across a wide range of viral pathogens. In a first aspect, the disclosure provides methods for determining the risk of a subject to severe outcome from exposure to infection based on genetic data which comprises; obtaining a fluid sample from the subject that contains DNA that encodes information about genetic ancestry admixture and immune response; extracting genotype data from DNA sample; and inputting the extracted genotype data into a prediction model to predict the probability of an individual to have severe outcome or death. In some embodiments, the genotype data includes a model to predict type I IFN level based on genetic ancestry admixture, including but not limited to regional European ancestry. In some embodiments, the infection is a viral infection. In some embodiments, the infection is a non-viral infection. In some embodiments, the genotype data is from a specific region of the DNA. In some embodiments, the fluid sample is blood or saliva, or other types of biological samples that contain DNA.

[0017] In some embodiments, the infection is viral hepatitis. In some embodiments, the infection is HIV. In some embodiments, the infection is Covid 19.

[0018] In some embodiments, the methods include using a genetic model based on ancestry informative markers from DNA in the sample to predict severe outcome from an infection. In some embodiments, the methods include predicting IFN 1 level based in part on ancestry informative markers in the fluid sample. In some embodiments, the severe outcome is organ failure or death. In some embodiments, the methods further include use of the method to select servicemen for duty in areas with high risk of infection. In some embodiments, the infection is tuberculosis.

[0019] In some embodiments, the regional European regional ancestry is determined using a validated set of European- American ancestry informative markers (AIMs). In some embodiments, the European- American ancestry informative markers (AIMs) consist of 275 SNPs.

[0020] In some embodiments, the methods further include providing appropriate treatment to a subject determined to be at high risk of severe outcome from exposure to infection. In some embodiments, the appropriate treatment is provided prior to the onset of infection. In some embodiments, the prediction model comprises the genetic ancestry admixture prediction model and the IFN level prediction model. In some embodiments, the prediction model comprises the IFN prediction model.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Methods and materials are described herein for use in the present invention; other, suitable methods and materials known in the art can also be used. The materials, methods, and examples are illustrative only and not intended to be limiting. All publications, patent applications, patents, sequences, database entries, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control.

[0022] Other features and advantages of the invention will be apparent from the following detailed description and figures, and from the claims.

[0023] DESCRIPTION OF DRAWINGS

[0024] FIG. 1 A shows a box-and- whisker plot of serum type I interferon (IFN) activity scores (multiples of standard deviation (SD) relative to healthy control) across ancestries show varying median levels and distributions in log scale. Abbreviations representing ancestries as follows; As-A: Asian American; AA: African American; HA: Hispanic American; EA: European American.

[0025] FIG. IB shows a box-and- whisker plot of type I interferon (IFN) activity across countries within the European ancestry in log scale. Statistically significant differences are observed between Sweden and Crete, and Euro- American and Crete sub-ancestral populations.

[0026] FIG. 2 A shows a plot of first principal component (PC A) of ancestry informative markers (AIMS) genotype data from Finnish (FIN) and Italian (TSI) populations, which segregates into two clusters.

[0027] FIG. 2B shows a plot of regularized logistic regression model providing stronger clustering for Finnish (FIN) and Italian (TSI) cohorts, and predicts US-European cohort (MT) population to have admixtures of FIN & TSI characteristics. FIG. 2C shows a plot of measured IFN scores and probability predictions of segregation into Finnish (FIN), US-European Within the US-European cohort, subjects with FIN dominant predicted admixture shows higher type I interferon activity average relative to the TSI dominant predicted admixture cohort.

[0028] FIG. 3 A shows a plot of predicted probability for a subject to have high type I IFN activity (>2 standard deviations), indicating a significant difference between high and low measured IFN cohorts.

[0029] FIG. 3B shows a plot of predicted probabilities of high IFN levels and of Finnish (FIN) population. Combining the FIN-TSI ancestry admixture model and the IFN level prediction model based on the US-European cohort shows a gradient of the medians with the FIN cohort having the highest IFN level.

[0030] FIG. 4A shows a plot of predicted probability of high IFN level across European sub-ancestral populations, indicating a gradient with Finnish (FIN) having the highest average high-IFN probability.

[0031] FIG. 4B shows a map-based schematic of predicted probability of high IFN level plotted on a geographical heat map, indicating an angular counter-clockwise gradient with the highest, intermediate, and lowest probability of high IFN level.

[0032] FIG. 4C shows a table of ratios of Mean(Prob(High IFN)) and t-test p values for each country pair.

[0033] FIG. 5A shows a plot of anti-correlations between Mean(Prob(IFN High)) and Fatality Rate per country for COVID-19.

[0034] FIG. 5B shows a plot indicating positive correlation between the ratio of CO VID- 19 fatality rates for 2022 (higher vaccination rate) to 2021, and the Mean(Prob(IFN High)). The ratios are less than 1, indicating a decrease in fatality rate as more people are vaccinated, with the ratio significantly lower for populations that have lower Mean(Prob(IFN High)) indicating a more significant vaccine effect in reducing the fatality rates.

[0035] FIG. 5C shows a plot of anti-correlations between Mean(Prob(IFN High)) and Fatality Rate per country for viral hepatitis. FIG. 5D shows a plot of anti-correlations between Mean(Prob(IFN High)) and Fatality Rate per country for HIV.

[0036] FIG. 6A shows a plot of predicted individual risk of death from viral infection across European sub-ancestral populations for COVID- 19.

[0037] FIG. 6B shows a plot of predicted individual risk of death from viral infection across European sub-ancestral populations for hepatitis.

[0038] FIG. 6C shows a plot of predicted individual risk of death from viral infection across European sub-ancestral populations for HIV.

[0039] FIG. 6D shows a plot comparing the mean of the predicted risk of death from COVID-19 for each country and actual reported fatality rate of COVID-19 for each country, indicating a significant positive correlation.

[0040] FIG. 6E shows a plot comparing the mean of the predicted risk of death from hepatitis for each country and actual reported fatality rate of hepatitis for each country, indicating a significant positive correlation.

[0041] FIG. 6F shows a plot comparing the mean of the predicted risk of death from HIV for each country and actual reported fatality rate of HIV for each country, indicating a significant positive correlation.

[0042] DETAILED DESCRIPTION

[0043] Genetic Variation

[0044] The genomic sequence within populations is not identical when individuals are compared. Rather, the genome exhibits sequence variability between individuals at many locations in the genome. Such variations in sequence are commonly referred to as polymorphisms, and there are many such sites within each genome For example, the human genome exhibits sequence variations which occur on average every 500 base pairs. The most common sequence variant consists of base variations at a single base position in the genome, and such sequence variants, or polymorphisms, are commonly called Single Nucleotide Polymorphisms ("SNPs"). These SNPs are believed to have occurred in a single mutational event, and therefore there are usually two possible alleles possible at each SNP site; the original allele and the mutated allele. Due to natural genetic drift and possibly also selective pressure, the original mutation has resulted in a polymorphism characterized by a particular frequency of its alleles in any given population. Many other types of sequence variants are found in the human genome, including microsatellites, insertions, deletions, inversions and copy number variations. A polymorphic microsatellite has multiple small repeats of bases (such as CA repeats, TG on the complimentary strand) at a particular site in which the number of repeat lengths varies in the general population. In general terms, each version of the sequence with respect to the polymorphic site represents a specific allele of the polymorphic site. These sequence variants can all be referred to as polymorphisms, occurring at specific polymorphic sites characteristic of the sequence variant in question. In general terms, polymorphisms can comprise any number of specific alleles. Thus in one embodiment of the methods disclosed herein, the polymorphism is characterized by the presence of two or more alleles in any given population. In another embodiment, the polymorphism is characterized by the presence of three or more alleles. In other embodiments, the polymorphism is characterized by four or more alleles, five or more alleles, six or more alleles, seven or more alleles, nine or more alleles, or ten or more alleles. All such polymorphisms can be utilized in the methods and kits of the present methods, and are thus within the scope of the methods.

[0045] In some instances, reference is made to different alleles at a polymorphic site without choosing a reference allele. Alternatively, a reference sequence can be referred to for a particular polymorphic site. The reference allele is sometimes referred to as the "wild-type" allele and it usually is chosen as either the first sequenced allele or as the allele from a "nonaffected" individual (e.g., an individual that does not display a trait or disease phenotype). Alleles for SNP markers as referred to herein refer to the bases A, C, G or T as they occur at the polymorphic site in the SNP assay employed. A person of ordinary skill in the art will recognize that by assaying or reading the opposite DNA strand, the complementary allele can in each case be measured. Thus, for a polymorphic site (polymorphic marker) containing an A / G polymorphism, the assay employed may either measure the percentage or ratio of the two bases possible, i.e. A and G. Alternatively, by designing an assay that determines the opposite strand on the DNA template, the percentage or ratio of the complementary bases T / C can be measured. Quantitatively (for example, in terms of relative risk), identical results would be obtained from measurement of either DNA strand ( + strand or - strand). Polymorphic sites (polymorphic markers) can allow for differences in sequences based on substitutions, insertions or deletions. For example, a polymorphic microsatellite has multiple small repeats of bases (such as CA repeats) at a particular site in which the number of repeat lengths varies in the general population. Each version of the sequence with respect to the polymorphic site represents a specific allele of the polymorphic site.

[0046] Typically, a reference sequence is referred to for a particular sequence. Alleles that differ from the reference are referred to as "variant" alleles. A variant sequence, as used herein, refers to a sequence that differs from the reference sequence but is otherwise substantially similar. Alleles at the polymorphic genetic markers that make up the haplotypes described herein are variants. Additional variants can include changes that affect a polypeptide. Sequence differences, when compared to a reference nucleotide sequence, can include the insertion or deletion of a single nucleotide, or of more than one nucleotide, resulting in a frame shift; the change of at least one nucleotide, resulting in a change in the encoded amino acid; the change of at least one nucleotide, resulting in the generation of a premature stop codon; the deletion of several nucleotides, resulting in a deletion of one or more amino acids encoded by the nucleotides; the insertion of one or several nucleotides, such as by unequal recombination or gene conversion, resulting in an interruption of the coding sequence of a reading frame; duplication of all or a part of a sequence; transposition; or a rearrangement of a nucleotide sequence, as described in detail herein. Such sequence changes alter the polypeptide encoded by the nucleic acid. For example, if the change in the nucleic acid sequence causes a frame shift, the frame shift can result in a change in the encoded amino acids, and / or can result in the generation of a premature stop codon, causing generation of a truncated polypeptide. Alternatively, a polymorphism associated with increased risk for severe or fatal outcome from a viral infection can be a synonymous change in one or more nucleotides (i.e., a change that does not result in a change in the amino acid sequence). Such a polymorphism can, for example, alter splice sites, affect the stability or transport of mRNA, or otherwise affect the transcription or translation of an encoded polypeptide. It can also alter DNA to increase the possibility that structural changes, such as amplifications or deletions, occur at the somatic level. The polypeptide encoded by the reference nucleotide sequence is the "reference" polypeptide with a particular reference amino acid sequence, and polypeptides encoded by variant alleles are referred to as "variant" polypeptides with variant amino acid sequences.

[0047] Detecting specific polymorphic markers and / or haplotypes can be accomplished by methods known in the art for detecting sequences at polymorphic sites. For example, standard techniques for genotyping for the presence of SNPs and / or microsatellite markers can be used, such as fluorescence-based techniques (e.g., Chen, X. et al., Genome Res. 9(5): 492-98 (1999); Kutyavin et al., Nucleic Acid Res. 34:el28 (2006)), utilizing PCR, LCR, Nested PCR and other techniques for nucleic acid amplification. Specific methodologies available for SNP genotyping include, but are not limited to, TaqMan genotyping assays and SNPlex platforms (Applied Biosystems), mass spectrometry (e.g., MassARRAY system from Sequenom), minisequencing methods, real-time PCR, Bio-Plex system (BioRad), CEQ and SNPstream systems (Beckman), Molecular Inversion Probe array technology (e.g., Affymetrix GeneChip), and BeadArray Technologies (e.g., Illumina GoldenGate and Infmium assays), SNP genotyping arrays, or next-generation sequencing technologies. By these or other methods available to the person skilled in the art, one or more alleles at polymorphic markers, including microsatellites, SNPs or other types of polymorphic markers, can be identified. In certain methods described herein, an individual who is at an increased susceptibility (i.e., at risk) for severe or fatal outcome from a viral infection is an individual in whom at least one specific allele at one or more polymorphic marker or haplotype conferring increased susceptibility for severe or fatal outcome from a viral infection is identified (i.e., at-risk marker alleles or haplotypes). In one aspect, the at-risk marker or haplotype is one that confers a significant increased risk (or susceptibility) of severe or fatal outcome from a viral infection. In one embodiment, significance associated with a marker or haplotype is measured by a relative risk. In one embodiment, significance associated with a marker or haplotype is measured by a relative risk (RR). In another embodiment, significance associated with a marker or haplotye is measured by an odds ratio (OR). In a further embodiment, the significance is measured by a percentage. In one embodiment, a significant increased risk is measured as a risk (relative risk and / or odds ratio) of at least 1.2, including but not limited to: at least 1.2, at least 1.3, at least 1.4, at least 1.5, at least 1.6, at least 1.7, 1.8, at least 1.9, at least 2.0, at least 2.5, at least 3.0, at least 4.0, and at least 5.0. In a particular embodiment, a risk (relative risk and / or odds ratio) of at least 1.2 is significant. In another particular embodiment, a risk of at least 1.3 is significant. In yet another embodiment, a risk of at least 1 .4 is significant. In a further embodiment, a relative risk of at least 1.5 is significant. In another further embodiment, a significant increase in risk is at least 1. 7 is significant. However, other cutoffs are also contemplated, e.g., at least 1.15, 1.25, 1.35, and so on, and such cutoffs are also within scope of the present invention. In other embodiments, a significant increase in risk is at least about 20%, including but not limited to about 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, and 500%. In one particular embodiment, a significant increase in risk is at least 20%. In other embodiments, a significant increase in risk is at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% and at least 100%. Other cutoffs or ranges as deemed suitable by the person skilled in the art to characterize the invention are however also contemplated, and those are also within scope of the present invention. In certain embodiments, a significant increase in risk is characterized by a p- value, such as a p:-value of less than 0.05, less than 0.01, less than 0.001, less than 0.0001, less than 0.00001, less than 0.000001, less than 0.0000001, less than 0.00000001, or less than 0.000000001.

[0048] An at-risk polymorphic marker or haplotype of the present invention is one where at least one allele of at least one marker or haplotype is more frequently present in an individual at risk for severe or fatal outcome from a viral infection (affected), compared to the frequency of its presence in a healthy individual (control), and wherein the presence of the marker or haplotype is indicative of susceptibility to severe or fatal outcome from a viral infection. The control group may in one embodiment be a population sample, i.e. a random sample from the general population. In another embodiment, the control group is represented by a group of individuals who are disease- free. Such disease-free control may in one embodiment be characterized by the absence of one or more specific disease-associated symptoms. In another embodiment, the disease-free control group is characterized by the absence of one or more disease-specific risk factors. Such risk factors are in one embodiment at least one environmental risk factor. Representative environmental factors are natural products, minerals or other chemicals which are known to affect, or contemplated to affect, the risk of developing the specific disease or trait. Other environmental risk factors are risk factors related to lifestyle, including but not limited to food and drink habits, geographical location of main habitat, and occupational risk factors. In another embodiment, the risk factors comprise at least one additional genetic risk factor.

[0049] An example of a simple test for correlation would be a Fisher-exact test on a two by two table. Given a cohort of chromosomes, the two by two table is constructed out of the number of chromosomes that include both of the markers or haplotypes, one of the markers or haplotypes but not the other and neither of the markers or haplotypes. Other statistical tests of association known to the skilled person are also contemplated and are also within scope of the invention.

[0050] In other embodiments of the invention, an individual who is at a decreased susceptibility (i.e., at a decreased risk) for a disease or trait is an individual in whom at least one specific allele at one or more polymorphic marker or haplotype conferring decreased susceptibility for the disease or trait is identified. The marker alleles and / or haplotypes conferring decreased risk are also said to be protective. In one aspect, the protective marker or haplotype is one that confers a significant decreased risk (or susceptibility) of the disease or trait. In one embodiment, significant decreased risk is measured as a relative risk (or odds ratio) of less than 0.9, including but not limited to less than 0.9, less than 0.8, less than 0.7, less than 0.6, less than 0.5, less than 0.4, less than 0.3, less than 0.2 and less than 0.1. In one particular embodiment, significant decreased risk is less than 0.7. In another embodiment, significant decreased risk is less than 0.5. In yet another embodiment, significant decreased risk is less than 0.3. In another embodiment, the decrease in risk (or susceptibility) is at least 20%, including but not limited to at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95% and at least 98%.

[0051] In one particular embodiment, a significant decrease in risk is at least about 30%. In another embodiment, a significant decrease in risk is at least about 50%. In another embodiment, the decrease in risk is at least about 70%. Other cutoffs or ranges as deemed suitable by the person skilled in the art to characterize the invention are however also contemplated, and those are also within scope of the present invention.

[0052] The person skilled in the art will appreciate that for markers with two alleles present in the population being studied (such as SNPs), and wherein one allele is found in increased frequency in a group of individuals with a trait or disease in the population, compared with controls, the other allele of the marker will be found in decreased frequency in the group of individuals with the trait or disease, compared with controls. In such a case, one allele of the marker (the one found in increased frequency in individuals with the trait or disease) will be the at-risk allele, while the other allele will be a protective allele.

[0053] A genetic variant associated with a disease or a trait (e g. severe or fatal outcome from a viral infection) can be used alone to predict the risk of the outcome for a given genotype. For a biallelic marker, such as a SNP, there are 3 possible genotypes: homozygote for the at risk variant, heterozygote, and non-carrier of the at risk variant. Risk associated with variants at multiple loci can be used to estimate overall risk. For multiple SNP variants, there are k possible genotypes (k = 3n x 2P); where n is the number autosomal loci and p the number of gonosomal (sex chromosomal) loci. Overall risk assessment calculations usually assume that the relative risks of different genetic variants multiply, i.e. the overall risk (e.g., RR or OR) associated with a particular genotype combination is the product of the risk values for the genotype at each locus. If the risk presented is the relative risk for a person, or a specific genotype for a person, compared to a reference population with matched gender and ethnicity, then the combined risk is the product of the locus specific risk values, and also corresponds to an overall risk estimate compared with the population. If the risk for a person is based on a comparison to non-carriers of the at-risk allele, then the combined risk corresponds to an estimate that compares the person with a given combination of genotypes at all loci to a group of individuals who do not carry risk variants at any of those loci. The group of noncarriers of any at risk variant has the lowest estimated risk and has a combined risk, compared with itself (i.e., non-carriers) of 1 .0, but has an overall risk, compare with the population, of less than 1.0. It should be noted that the group of non-carriers can potentially be very small, especially for large number of loci, and in that case, its relevance is correspondingly small.

[0054] Risk assessment and Diagnostics

[0055] Within any given population, there is an absolute risk of developing a disease or trait, e.g., severe or fatal outcome from a viral infection, defined as the chance of a person developing the specific disease or trait over a specified time period. Risk is typically measured by looking at very large numbers of people, rather than at a particular individual. Risk is often presented in terms of Absolute Risk (AR) and Relative Risk (RR).

[0056] Relative Risk is used to compare risks associating with two variants or the risks of two different groups of people. For example, it can be used to compare a group of people with a certain genotype with another group having a different genotype. For a disease, a relative risk of 2 means that one group has twice the chance of developing a disease as the other group. The Risk presented is usually the relative risk for a person, or a specific genotype of a person, compared to the population with matched gender and ethnicity. Risks of two individuals of the same gender and ethnicity could be compared in a simple manner. For example, if, compared to the population, the first individual has relative risk 1.5 and the second has relative risk 0.5, then the risk of the first individual compared to the second individual is 1.5 / 0.5 = 3.

[0057] As described herein, certain polymorphic markers and haplotypes comprising such markers are found to be useful for risk assessment of severe or fatal outcome from a viral infection. Risk assessment can involve the use of the markers for diagnosing a susceptibility to the severe or fatal outcome from a viral infection. Particular alleles of polymorphic markers are found more frequently in individuals with severe or fatal outcome from a viral infection, than in individuals without diagnosis of severe or fatal outcome from a viral infection. Therefore, these marker alleles have predictive value for detecting severe or fatal outcome from a viral infection, or a susceptibility to severe or fatal outcome from a viral infection, in an individual. Tagging markers within haplotype blocks or LD blocks comprising at-risk markers, such as the markers of the methods disclosed herein, can be used as surrogates for other markers and / or haplotypes within the haplotype block or LD block. Markers with values of r2 equal to 1 are perfect surrogates for the at-risk variants, i.e. genotypes for one marker perfectly predicts genotypes for the other. Markers with smaller values of r2 than 1 can also be surrogates for the at-risk variant, or alternatively represent variants with relative risk values as high as or possibly even higher than the at-risk variant. The at-risk variant identified may not be the functional variant itself, but is in this instance in linkage disequilibrium with the true functional variant. The present methods encompass the assessment of such surrogate markers for the markers as disclosed herein. Such markers are annotated, mapped and listed in public databases, as well known to the skilled person, or can alternatively be readily identified by sequencing the region or a part of the region identified by the markers of the present invention in a group of individuals, and identify polymorphisms in the resulting group of sequences. As a consequence, the person skilled in the art can readily and without undue experimentation genotype surrogate markers in linkage disequilibrium with the markers and / or haplotypes as described herein. The tagging or surrogate markers in LD with the at-risk variants detected, also have predictive value for detecting association to a severe or fatal outcome from a viral infection, or a susceptibility to a severe or fatal outcome from a viral infection, in an individual. These tagging or surrogate markers that are in LD with the markers of the present invention can also include other markers that distinguish among haplotypes, as these similarly have predictive value for detecting susceptibility to severe or fatal outcome from a viral infection. The present invention can in certain embodiments be practiced by assessing a sample comprising genomic DNA from an individual for the presence of variants described herein to be associated with severe or fatal outcome from a viral infection. Such assessment includes steps of detecting the presence or absence of at least one allele of at least one polymorphic marker, using methods well known to the skilled person and further described herein, and based on the outcome of such assessment, determine whether the individual from whom the sample is derived is at increased or decreased risk (increased or decreased susceptibility) of severe or fatal outcome from a viral infection. Alternatively, the invention can be practiced utilizing a dataset comprising information about the genotype status of at least one polymorphic marker described herein to be associated with severe or fatal outcome from a viral infection (or markers in linkage disequilibrium with at least one marker shown herein to be associated with severe or fatal outcome from a viral infection). In other words, a dataset containing information about such genetic status, for example in the form of genotype counts at a certain polymorphic marker, or a plurality of markers (e.g., an indication of the presence or absence of certain at-risk alleles), or actual genotypes for one or more markers, can be queried for the presence or absence of certain at-risk alleles at certain polymorphic markers shown by the present inventors to be associated with severe or fatal outcome from a viral infection. A positive result for a variant (e.g., marker allele) associated with severe or fatal outcome from a viral infection, as shown herein, is indicative of the individual from which the dataset is derived is at increased susceptibility (increased risk) of severe or fatal outcome from a viral infection. Genetic Testing

[0058] The person skilled in the art will appreciate and understand that the variants described herein in general do not, by themselves, provide an absolute identification of individuals who will develop a severe or fatal outcome from a viral infection. The variants described herein do however indicate increased and / or decreased likelihood that individuals carrying the at-risk or protective variants of the invention will develop symptoms associated with severe or fatal outcome from a viral infection. This information is however extremely valuable in itself, as outlined in more detail in the below, as it can be used to, for example, initiate preventive measures, so as to be able to apply treatment at an early stage. The knowledge about a genetic variant that confers a risk of developing severe or fatal outcome from a viral infection offers the opportunity to apply a genetic test to distinguish between individuals with severe or fatal outcome from a viral infection (i.e. carriers of the at-risk variant) and those with decreased risk of developing the severe or fatal outcome from a viral infection (i.e. carriers of the protective variant). The core values of genetic testing, for individuals belonging to both of the above mentioned groups, are the possibilities of being able to diagnose disease, or a predisposition to disease, at an early stage and provide information to the clinician about prognosis / aggressiveness of disease in order to be able to apply the most appropriate treatment.

[0059] The present methods can thus be used for risk assessment for severe or fatal outcome from a viral infection. The polymorphic markers of the present methods can be used alone or in combination, as well as in combination with other factors, including known biomarkers, for risk assessment of an individual for severe or fatal outcome from a viral infection. Many factors known to affect the predisposition of individuals towards developing risk of severe or fatal outcome from a viral infection are known to the person skilled in the art and can be utilized in such assessment.

[0060] Viral Hepatitis Viral hepatitis involves liver inflammation due to a viral infection. It may present in acute form as a recent infection with relatively rapid onset, or in chronic form, typically progressing from a long-lasting asymptomatic condition up to a decompensated hepatic disease and hepatocellular carcinoma (HCC).

[0061] The most common causes of viral hepatitis are the five unrelated hepatotropic viruses hepatitis A, B, C, D, and E. Other viruses can also cause liver inflammation, including cytomegalovirus, Epstein-Barr virus, and yellow fever. There also have been scores of recorded cases of viral hepatitis caused by herpes simplex virus. The most common cause of hepatitis is viral. Although the effects of various viruses are all classified under the disease hepatitis, these viruses are not all related.

[0062] Hepatitis A or infectious jaundice is caused by hepatitis A virus (HAV), a picornavirus transmitted by the fecal-oral route often associated with ingestion of contaminated food. It causes an acute form of hepatitis and does not have a chronic stage. A patient's immune system makes antibodies against HAV that confer immunity against future infection. People with hepatitis A are advised to rest, stay hydrated and avoid alcohol. A vaccine is available that will prevent HAV infection for up to 10 years. Hepatitis A can be spread through personal contact, consumption of raw sea food, or drinking contaminated water. This occurs primarily in third world countries. Strict personal hygiene and the avoidance of raw and unpeeled foods can help prevent an infection. Infected people excrete HAV with their feces two weeks before and one week after the appearance of jaundice. The time between the infection and the start of the illness averages 28 days. Most patients recover fully within 2 months, although approximately 15% of affected people may experience continuous or relapsing symptoms from six months to a year following initial diagnosis.

[0063] Hepatitis B is caused by the hepatitis B virus, a hepadnavirus that can cause both acute and chronic hepatitis. Chronic hepatitis develops in the 15% of adults who are unable to eliminate the virus after an initial infection. Identified methods of transmission include contact with blood, blood transfusion (now rare), unsanitary tattoos, sex (through sexual intercourse or contact with bodily fluids), or mother-to-child by breast feeding. Patients with chronic hepatitis B have antibodies against the virus, but not enough to clear the infected liver cells. Hepatitis B is endemic in a number of (mainly South-East Asian) countries.

[0064] Hepatitis C is caused by hepatitis C virus (HCV), an RNA virus of the family Flaviviridae. HCV can be transmitted through contact with blood (including through sexual contact if the two parties' blood is mixed) and can also cross the placenta. Hepatitis C usually leads to chronic hepatitis, culminating in cirrhosis in some people. It usually remains asymptomatic for decades. Patients with hepatitis C are susceptible to severe hepatitis if they contract either hepatitis A or B, so all persons with hepatitis C should be immunized against hepatitis A and hepatitis B if they are not already immune, and avoid alcohol. HCV can lead to the development of hepatocellular carcinoma, however, only a minority of HCV-infected individuals develop cancer (1-4% annually), suggesting a complex interplay between viral gene expression and host and environmental factors to promote carcinogenesis. The risk is increased two-fold with active HBV coinfection and a 21% increase in mortality compared to those with latent HBV and HCV. HCV viral levels can be reduced to undetectable levels by a combination of interferon and the antiviral drug ribavirin. The genotype of the virus is the primary determinant of the rate of response to this treatment regimen, with genotype 1 being the most resistant.

[0065] Hepatitis C is the most common chronic bloodborne infection in the United States, and the leading cause of liver transplants.

[0066] Hepatitis D is caused by the hepatitis D virus (HDV), or hepatitis delta virus; it belongs to the genus Deltavirus. HDV is similar to a satellite virus as it can only propagate in the presence of the hepatitis B virus, depending on the helper function of HBV for its replication and expression. It has no independent life cycle, but can survive and replicate as long as HBV infection persists in the host body. It can only cause infection when encapsulated by hepatitis B virus surface antigens. The vaccine for hepatitis B protects against hepatitis D virus because of the latter's dependence on the presence of hepatitis B virus for it to replicate. Hepatitis E is caused by the Hepatitis E virus (HEV), from the family Hepeviridae. It produces symptoms similar to hepatitis A, although it can take a fulminant course in some patients, particularly pregnant women (mortality rate about 20%); chronic infections may occur in immune-compromised patients. It is more prevalent in the Indian subcontinent. The virus is feco-orally transmitted and is usually self-limited.

[0067] HIV

[0068] The human immunodeficiency viruses (HIV) are two species of Lentivirus (a subgroup of retrovirus) that infect humans. Over time, they cause acquired immunodeficiency syndrome (AIDS), a condition in which progressive failure of the immune system allows life-threatening opportunistic infections and cancers to thrive. Without treatment, the average survival time after infection with HIV is estimated to be 9 to 11 years, depending on the HIV subtype.

[0069] In most cases, HIV is a sexually transmitted infection and occurs by contact with or transfer of blood, pre-ejaculate, semen, and vaginal fluids. Non-sexual transmission can occur from an infected mother to her infant during pregnancy, during childbirth by exposure to her blood or vaginal fluid, and through breast milk. Within these bodily fluids, HIV is present as both free virus particles and virus within infected immune cells. Research has shown (for both same-sex and opposite-sex couples) that HIV is untransmittable through condomless sexual intercourse if the HIV-positive partner has a consistently undetectable viral load.

[0070] HIV infects vital cells in the human immune system, such as helper T cells (specifically CD4+ T cells), macrophages, and dendritic cells. HIV infection leads to low levels of CD4+ T cells through a number of mechanisms, including pyroptosis of abortively infected T cells, apoptosis of uninfected bystander cells, direct viral killing of infected cells, and killing of infected CD4+ T cells by CD8+ cytotoxic lymphocytes that recognize infected cells. When CD4+ T cell numbers decline below a critical level, cell- mediated immunity is lost, and the body becomes progressively more susceptible to opportunistic infections, leading to the development of AIDS.

[0071] COVID-19

[0072] Coronavirus disease 2019 (COVID- 19) is a contagious disease caused by the coronavirus SARS-CoV-2. The first known case was identified in Wuhan, China, in December 2019. The symptoms of COVID-19 are variable but often include fever, fatigue, cough, breathing difficulties, loss of smell, and loss of taste. Symptoms may begin one to fourteen days after exposure to the virus. At least a third of people who are infected do not develop noticeable symptoms. Of those who develop symptoms noticeable enough to be classified as patients, most (81%) develop mild to moderate symptoms (up to mild pneumonia), while 14% develop severe symptoms (dyspnea, hypoxia, or more than 50% lung involvement on imaging), and 5% develop critical symptoms (respiratory failure, shock, or multiorgan dysfunction). Older people are at a higher risk of developing severe symptoms. Some complications result in death. Some people continue to experience a range of effects (long COVID) for months or years after infection, and damage to organs has been observed.

[0021] Multi-year studies are underway to further investigate the long-term effects of the disease.

[0073] COVID- 19 transmission occurs when infectious particles are breathed in or come into contact with the eyes, nose, or mouth. The risk is highest when people are in close proximity, but small airborne particles containing the virus can remain suspended in the air and travel over longer distances, particularly indoors. Transmission can also occur when people touch their eyes, nose or mouth after touching surfaces or objects that have been contaminated by the virus. People remain contagious for up to 20 days and can spread the virus even if they do not develop symptoms.

[0074] Testing methods for COVID-19 to detect the virus's nucleic acid include real-time reverse transcription polymerase chain reaction (RT-PCR), transcription-mediated amplification, and reverse transcription loop-mediated isothermal amplification (RT-LAMP) from a nasopharyngeal swab. Several COVID-19 vaccines have been approved and distributed in various countries, many of which have initiated mass vaccination campaigns. Other preventive measures include physical or social distancing, quarantining, ventilation of indoor spaces, use of face masks or coverings in public, covering coughs and sneezes, hand washing, and keeping unwashed hands away from the face. While drugs have been developed to inhibit the virus, the primary treatment is still symptomatic, managing the disease through supportive care, isolation, and experimental measures.

[0075] Methods of Treatment

[0076] The methods disclosed herein contemplate administration of an effective amount of a compound or composition to achieve the desired or stated effect. In some embodiments, the compound or composition is a vaccine. In some embodiments, the compound or composition is an antiviral treatment. In some embodiments, the compound or composition is administered to an individual that has been determined by the methods disclosed herein to be at high risk of severe outcome of a viral infection. In some embodiments, the compound or composition is administered to an individual that has been predicted to have elevated IFN production or gene expression in response to viral infection. In some embodiments, the compound or composition is administered to an individual that is predicted to be at high risk of severe outcome of viral hepatitis. In some embodiments, the compound or composition is administered to an individual that is predicted to be at high risk of severe outcome of HIV infection. In some embodiments, the compound or composition is administered to an individual that is predicted to be at high risk of severe outcome of COVID-19. The amount of active ingredient that can be combined with the carrier materials to produce a single dosage form will vary depending upon the host treated and the particular mode of administration.

[0077] In some aspects, the present disclosure provides methods for using a composition comprising a compound, including pharmaceutical compositions (indicated below as ‘X’) disclosed herein in the following methods: Substance X for use as a medicament in the treatment of individuals predicted by a genetic assay disclosed herein to be at high risk of severe outcome of one or more viral infections disclosed herein. Use of substance X for the manufacture of a medicament for the treatment of Y; and substance X for use in the treatment of Y. In some embodiments, X is a vaccine. In some embodiments, X is an antiviral compound or composition.

[0078] In some aspects, the methods disclosed include the administration of a therapeutically effective amount of one or more of the compounds or compositions described herein to a subject (e.g., a mammalian subject, e.g., a human subject) who is in need of, or who has been determined to be in need of, such treatment. In some aspects, the methods disclosed include selecting a subject and administering to the subject an effective amount of one or more of the compounds or compositions described herein, and optionally repeating administration as required for the prevention or treatment of viral infection or diseases related to viral infection.

[0079] In some aspects, subject selection can include obtaining a sample from a subject (e.g., a candidate subject) and testing the sample for an indication that the subject is suitable for selection. In some aspects, the subject can be confirmed or identified, e.g. by a health care professional, as being at high risk of severe outcome of a viral infection. In some aspects, multiple parties can be included in subject selection. For example, a first party can obtain a sample from a candidate subject and a second party can test the sample. In some aspects, subjects can be selected or referred by a medical practitioner (e.g., a general practitioner). In some aspects, subject selection can include obtaining a sample from a selected subject and storing the sample or using the in the methods disclosed herein. Samples can include, e.g., cells or populations of cells, blood, genomic DNA isolated from a sample, and the like.

[0080] In some aspects, methods of treatment can include a single administration, multiple administrations, and repeating administration of one or more compounds disclosed herein as required for the prevention or treatment of the viral infection or disease of which the subject has been predicted to be at high risk for severe outcomes. In some aspects, methods of treatment can include assessing a level of disease in the subject prior to treatment, during treatment, or after treatment. In some aspects, treatment can continue until a decrease in the level of disease in the subject is detected.

[0081] The term “subject,” as used herein, refers to any animal. In some instances, the subject is a mammal. In some instances, the term “subject,” as used herein, refers to a human (e.g., a man, a woman, or a child).

[0082] The terms “administer,” “administering,” or “administration,” as used herein, refer to implanting, ingesting, injecting, inhaling, or otherwise absorbing a compound or composition, regardless of form. For example, the methods disclosed herein include administration of an effective amount of a compound or composition to achieve the desired or stated effect.

[0083] The terms “treat”, “treating,” or “treatment,” as used herein, refer to partially or completely alleviating, inhibiting, ameliorating, or relieving the disease or condition from which the subject is suffering. This means any manner in which one or more of the symptoms of a disease or disorder are ameliorated or otherwise beneficially altered. As used herein, amelioration of the symptoms of a particular disorder refers to any lessening, whether permanent or temporary, lasting or transient that can be attributed to or associated with treatment by the compositions and methods of the present invention.

[0084] The terms “prevent,” “preventing,” and “prevention,” as used herein, shall refer to a decrease in the occurrence of a disease or decrease in the risk of acquiring a disease or its associated symptoms in a subject. The prevention may be complete, e.g., the total absence of disease or pathological cells in a subject. The prevention may also be partial, such that the occurrence of the disease or pathological cells in a subject is less than, occurs later than, or develops more slowly than that which would have occurred without the present invention.

[0085] As used herein, the term “preventing a disease” in a subject means for example, to stop the development of one or more symptoms of a disease in a subject before they occur or are detectable, e.g., by the patient or the patient’s doctor. Preferably, the disease does not develop at all, i.e., no symptoms of the disease are detectable. However, it can also mean delaying or slowing of the development of one or more symptoms of the disease. Alternatively, or in addition, it can mean decreasing the severity of one or more subsequently developed symptoms.

[0086] Specific dosage and treatment regimens for any particular patient will depend upon a variety of factors, including the activity of the specific compound employed, the age, body weight, general health status, sex, diet, time of administration, rate of excretion, drug combination, the severity and course of the disease, condition or symptoms, the patient’s disposition to the disease, condition or symptoms, and the judgment of the treating physician.

[0087] An effective amount can be administered in one or more administrations, applications or dosages. A therapeutically effective amount of a therapeutic compound (i.e., an effective dosage) depends on the therapeutic compounds selected. Moreover, treatment of a subject with a therapeutically effective amount of the compounds or compositions described herein can include a single treatment or a series of treatments. For example, effective amounts can be administered at least once. The compositions can be administered one from one or more times per day to one or more times per week; including once every other day. The skilled artisan will appreciate that certain factors can influence the dosage and timing required to effectively treat a subject, including but not limited to the severity of the disease or disorder, previous treatments, the general health or age of the subject, and other diseases present.

[0088] Following administration, the subject can be evaluated to detect, assess, or determine their level of disease. In some instances, treatment can continue until a change (e.g., reduction) in the level of disease in the subject is detected. Upon improvement of a patient’s condition (e.g., a change (e.g, decrease) in the level of disease in the subject), a maintenance dose of a compound, or composition disclosed herein can be administered, if necessary. Subsequently, the dosage or frequency of administration, or both, can be reduced, e.g., as a function of the symptoms, to a level at which the improved condition is retained. Patients may, however, require intermittent treatment on a long-term basis upon any recurrence of disease symptoms. EXAMPLES

[0089] The invention is further described in the following examples, which do not limit the scope of the invention described in the claims.

[0090] Materials and Methods

[0091] Subjects

[0092] Serum samples were obtained from 605 SLE patients (348 European-American, from the University of Chicago and Mayo Clinic, 204 Sweden SLE patients from Karolinska Institute, and 53 patients from Crete recruited at the University of Crete). All patients met the American College of Rheumatology classification criteria for SLE. Healthy population genotype data of European ancestries were obtained for 451 subjects from Harvard Medical School and 501 subjects from the 1000 Genomes study consortium project. The study was approved by the institutional review boards at each of the respective institutions.

[0093] Serum / FNa activity measurement

[0094] A sensitive and reproducible bioassay developed by our group was used to detect serum IFN-a activity, where reporter cells (WISH cells) are used to measure the ability of sera to cause IFN-induced gene transcription. The reporter cells are cultured with patient sera for 6 hours and then lysed, and three canonical IFN-a-induced transcripts (IFIT-I, MX-1, and PKR) are measured using rtPCR. Relative expression data from the three transcripts are then normalized using the mean and standard deviation of healthy donor sera run in the same assay, and data are presented as an IFN-a activity score. A cutoff point for the IFN-a activity score of two standard deviations above the mean of healthy donors are used to group IFN-a activity score into high vs low levels.

[0095] Genotyping

[0096] A validated set of European- American ancestry informative markers (AIMs) consisting of 275 SNPs

[0024] (See SNP panel above) designed to distinguish northwest and southeast European ancestry was used to assess the admixture proportions of Northern vs Southern European ancestries, and in the IFN level and viral infection fatality rate prediction models in this study. For the European-American cohort, subjects were genotyped on the Fluidigm Biomark microfluidic PCR genotyping system. The Harvard cohort was genotyped using the homogeneous MassEXTEND (hME) and iPLEX assays for the Sequenom MassARRAY platform. The healthy population genotype data is collected from the 1000 Genomes project consortium.

[0097] Statistical analysis

[0098] A principal component analysis (PCA) was performed to reduce the dimensions of the data from the 275 AIMs and used to infer each subject’s regional European ancestry and admixture. More than 90% of the variance in the data set was accounted for by the first 120 principal components. A logistic regression model with optimized elastic net regularization trained with cross-validation is used to predict the ancestry admixture proportion (Northern vs Southern) characteristic of each individual using the top 120 AIMs principal components, and used as a classifier to segregate N-S population with FIN and TSI as the outcome classes representing Northern and Southern ancestries respectively. The IFN level depiction model is based on a regularized logistic regression model with backward elimination that reduced the initial 120 AIMs principal components to 19 that are significant, is used to predict the probability of each subject to have a high IFN level. A Student’s t-test was used to determine whether the difference in the mean probability of high IFN level between select two groups of the population is statistically significant.

[0099] EXAMPLE 1: IFN level variation across ancestries in SLE

[0100] IFN level varies across ancestries in SLE where the average type I IFN activity in European-American SLE patients is lower than in the Asian-American, African- American, and Hispanic-American ancestry SLE cohorts. Here, we measured a comparison of type I interferon levels across European countries and European- American SLE cohorts using a functional reporter assay (see Methods, above, for details), as shown in FIG. 1. The Swedish cohort had a higher mean type I IFN level compared to Crete (p = 1.5 x 10'3), and European- American SLE patients had higher IFN levels than patients from Crete (p = 2. 1 x 10-2). The Swedish and Crete cohorts represent Northern and Southern European geographical areas respectively, and European- American cohort represents a group of subjects with varying degrees of admixture between Northern and Southern European genetic ancestiy.

[0101] EXAMPLE 2: Regional European ancestry determination

[0102] We genotyped 275 AIM SNPs in the 348 European- American SLE patients that are informative for regional European ancestry. These genotyped SNPs are listed below.

[0103] These 275 SNPs are from a panel of 300 informative markers for European ancestry. These SNPs overlap with genotype data sets from Harvard Medical School and the International Genome Sample Resource, 1000 Genomes Project cohorts. We then performed a principal component analysis (PCA) of the AIM SNP data from the SLE patients along with reference populations from the 1000 Genomes project from the Finnish (FIN) and Italian (TSI) populations. The first principal component (PCI) clearly segregates the Northern (FIN) and Southern (TSI) European cohort data as expected (results shown in FIG. 2A).

[0104] A regularized logistic regression model (Logist( (-0.53959881638244) + 4.57626483107339 * PCI + -1.75007916814067 * PC52 1 - Logist( (- 0.53959881638244) + 4.57626483107339 * PCI + -1.75007916814067 * PC52) was developed to predict the regional European ancestry (Northern vs. Southern) characteristic of each subject, trained using cross-validation, using the top 120 principal components from the PCA model (with >90% variance coverage) with FIN vs. TSI as the outcome variable. As shown in FIG. 2B, the prediction model strongly separates the FIN and TSI cohorts and demonstrates the varying degree of Northern vs. Southern European admixture present in the European-American subjects. Proportional degree of Northern vs. Southern European ancestry' is associated with type I IFN level in European -American SLE patients.

[0105] Given the potential for geographic and other factors to confound the relationship between world populations and type I IFN levels, we next compared the proportional Northern vs. Southern European genetic admixtures in the European- American SLE cohort with the measured type I IFN activity. This has the benefit of providing some degree of environmental control, as the chromosomes in admixed individuals share the same environment. We observed that subjects with greater proportional Northern European ancestry have a higher average IFN level (mean = 8.18) compared to subjects with more Southern ancestry (mean = 4.10), see FIG. 2C. This result aligns with the Northern-Southern IFN level gradient measured in the Sweden and Crete cohorts respectively.

[0106] EXAMPLE 3: IFN level prediction model based on AIMs

[0107] Next, we developed a model to predict type I IFN level based on the 275 European ancestry AIM SNPs. A total of 112 principal components that accounted for >90% of variance was trained with a backward regression model to predict IFN level (high vss low, with a threshold of two standard deviations). The components were reduced to 19 principal components after backward elimination with the AIC validation method. The trained model can be used to predict IFN level with AUC = 0.73 and p = 6. 1 x 10‘b. This linear combination of 19 principal components shows a strong significant difference in predicted IFN level for the measured high vs. low IFN European-American groups with t-test p-value of 3.4 x 10'11(results shown in FIG. 3 A). Combining the genetic ancestry admixture prediction model and the IFN level prediction model, we observe a gradient in predicted IFN level with the Northern (FIN) cohort having the highest probability of high IFN level, followed by the European-American cohort (with the more Northern-like sub-ancestry group having a higher IFN level than the more Southern-like sub-ancestry group), and the Southern (TSI) cohort, see results in FIG. 3B.

[0108] EXAMPLE 4: Relationship between European sub-ancestries and IFN levels

[0109] We applied the IFN prediction model to genotype data from European populations from the 1000 Genomes Project, including independent cohorts that were not used in the model training that include European sub-ancestries from Utah residents with Northern and Western European ancestry (CEU), Iberian populations in Spain (IBS), British from England and Scotland (GBR), Greek, Ashkenazi Jewish, and Polish. The predicted probability of high IFN level for the individual subjects are shown as box plots along with the mean values for each cohort in FIG. 4A. Pairwise t-test results are summarized in a table in FIG. 4C. Plotting this on a geographical map, we observe a gradient across the Northwest-Southeast direction, where the Northwest populations have higher probabilities of high IFN level (FIG. 4B). The CELT cohort is represented by Netherlands given the known ancestral genetic similarity between the two cohorts in the European map in FIG. 4B, as well as in the viral infection fatality correlation analysis in the proceeding sections.

[0110] EXAMPLE 5: Relationship between predicted IFN level and viral infection outcome severity Type I interferon is a critical part of the immune system against viral infections. In examining country-level viral outcomes data, we observed significant correlations between predicted type I IFN level based upon our regional ancestry model and fatalityrate related to viral infection (COVID-19, viral hepatitis, HIV). The results are shown in FIGs. 5A-5D.

[0111] FIG. 5 A shows the mean of probability of high IFN level against the fatality rate for COVID- 19 cases for each of the 7 European countries analyzed (Finland, Greece, Ireland, Italy, Netherlands, Poland, Spain), with the correlation coefficient (r ~ -0.79) and p-value (p=0.036). The variations in the fatality rate and mean probability of high IFN level between two distant countries (Netherlands and Poland) are 6.3-fold and 4.5-fold respectively as shown on the figure, highlighting the significant potential difference in fatality between these countries that corresponds to the predicted IFN level. FIG. 5B shows the ratio of fatality rates in 2022 to the fatality rates in 2021 on the y-axis, where the population vaccination rates are significantly higher in 2022 relative to 2021 Here, five countries that have >80% vaccination rates in 2022 are included (Greece, Spain, Italy, Finland, and Ireland) and 2 countries are excluded: Poland (66%) and Netherlands (unknown vaccination rate in 2022) to minimize bias. On the x-axis, is the mean probability of high IFN level for each country. Interestingly, we see a positive correlation (r=0.995, p=0.0004) between the ratio and the mean probability of high IFN level, indicating that the vaccination makes the biggest difference when the IFN level is lower on average. This is consistent with the hypothesis that higher IFN level provides stronger natural immunity even without the vaccines, and thus the additional protection by the vaccines is not as large as in the case for lower IFN level populations

[0112] FIG. 5C shows a similar plot as in FIG. 5A, for viral hepatitis infections, with r = -0.936 and p = 0.006, for Finland, Greece, Ireland, Italy, Netherlands, Spain. Here, the difference in fatality rate between predicted IFN level at the population level is significantly higher, with a large 97-fold difference between the highest to lowest fatality rates associated with just a 2.2-fold increase in the mean probability of high IFN level. The significantly higher sensitivity for hepatitis compared to HIV and COVID- 19 may relate to a larger impact of type I IFN in limiting viral hepatitis as compared to HIV and COVID-19.

[0113] FIG. 5D shows a similar plot as in FIG. 5 A, for HIV infections, where the countries are separated into two groups that geographically correspond to a North-South (Finland, Italy, Netherlands, Spain) and East-West (Greece, Poland, UK) gradients. We postulate that there are confounding factors that lead to different sensitivity of fatality to IFN level for the two cohorts. Each of the two groups show significant anti-correlation (r=-0.992, p=0.08) and (r=-0.924, p=0.076) for the East-West and North-South groups respectively. The sensitivity of the fatality rate to the mean probability of high IFN level for the North-South group is higher than the East-West group.

[0114] EXAMPLE 6: Predicted risk of death from viral infections

[0115] Combining the model that predicts IFN level based on AIM genotype principal components, and the model that predict viral infection fatality rate based on IFN level, here we predict the fatality rates of COVID-19, hepatitis, and HIV infections for each of 952 subjects based on the genotype data in the 1000 Genomes study and Harvard cohorts.

[0116] The fatality rate represents the probability of an individual to die if infected with the virus. FIGs. 6A-6C show the prediction results as box plots with a line connecting the mean value for each sub-ancestry. Supplementary tables for each of FIGs. 6A-6C are provided below.

[0117] Supplementary table for fig 6.a. Supplementary table for fig 6.b. FIGs. 6D-6F show correlations between the averaged predicted and actual fatality rates for each country for COVID-19, hepatitis, and HIV viral infections respectively. OTHER EMBODIMENTS

[0118] It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1. A method for determining the risk of a subject to severe outcome from exposure to infection based on genetic data which comprises; obtaining a fluid sample from the subject that contains DNA that encodes information about genetic ancestry admixture and immune response; extracting genotype data from DNA sample, and inputting the extracted genotype data into a prediction model to predict the probability of an individual to have severe outcome or death.

2. The method of claim 1 wherein the genotype data includes a model to predict type I IFN level based on genetic ancestry admixture, including but not limited to regional European ancestry.

3. The method of claim 1 wherein the infection is a viral infection.

4. The method of claim 1 wherein the infection is a non-viral infection.

5. The method of claim 1 wherein the genotype data is from a specific region of theDNA.

6. The method of claim 1 wherein the fluid sample is blood or saliva, or other types of biological samples that contain DNA.

7. The method of claim 1 wherein the infection is viral hepatitis.

8. The method of claim 1 wherein the infection is HIV.

9. The method of claim 1 wherein the infection is Covid 19.

10. The method of claim 1 which comprises using a genetic model based on ancestry informative markers from DNA in the sample to predict severe outcome from an infection.

11. The method of claim 1 which comprises predicting IFN 1 level based in part on ancestry informative markers in the fluid sample.

12. The method of claim 1 wherein the severe outcome is organ failure or death.

13. The method of claim 1 further comprising use of the method to select servicemen for duty in areas with high risk of infection.

14. The method of claim 1 wherein the infection is tuberculosis.

15. The method of claim 2 wherein the regional European regional ancestry is determined using a validated set of European- American ancestry informative markers (AIMs).

16. The method of claim 14 wherein the European- American ancestry informative markers (AIMs) consist of 275 SNPs.

17. The method of claim 1 which further comprises providing appropriate treatment to a subject determined to be at high risk of severe outcome from exposure to infection.

18. The method of claim 17 wherein the appropriate treatment is provided prior to the onset of infection.

19. The method of claim 1 wherein the prediction model comprises the genetic ancestry admixture prediction model and the IFN level prediction model.

20. The method of claim 1 wherein the prediction model comprises the IFN prediction model.

Images