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Host Genetics, Population Diversity, and Dengue Infection: An Unsolved Paradigm

Submitted:

02 October 2026

Posted:

05 October 2026

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Abstract
This narrative review examines recent literature on human genetic variation and the clinical spectrum of dengue. A comprehensive search through September 2026 synthesized findings from genetic association studies, HLA typing, and genome-wide studies. The evidence is systematically categorized according to the World Health Organization clinical classification. The majority of available data derive from investigations conducted in Southeast Asia, with limited contributions from Africa and Latin America. Notably, specific HLA alleles—particularly HLA-A*24—as well as MICB and PLCE1 gene variants demonstrate the strongest associations with severe dengue; however, these associations vary by population and viral serotype. Other immune response genes, including CD209, FCGR2A, and TNF, have also been implicated, although their effects exhibit inconsistency across diverse cohorts and epidemiological settings. Conversely, the impact of certain variants, such as FCGR2A R/R131, appears to be modulated by population context, infecting serotype, and infection history. A major limitation of the existing body of research is the prevalence of small sample sizes, heterogeneity in case definitions across guidelines, and insufficient adjustment for genetic diversity. To date, no genetic marker has been validated for routine clinical use on a global scale; nevertheless, large-scale genetic analyses have yielded novel insights that warrant further investigation in large, multi-ethnic studies integrating both host and viral genomic data. Genetic analyses are crucial for improving vaccine efficacy and for identifying therapeutic targets to prevent dengue infection and reduce the risk of severe disease.
Keywords: 
dengue
;  
severe dengue
;  
host genetic susceptibility
;  
immunogenetics
;  
genetic association study
;  
endemic regions
;  
bioinformatic analysis
Subject: 
Medicine and Pharmacology  -   Immunology and Allergy

1. Introduction

Dengue is a mosquito-borne viral infection endemic to more than 100 countries and occurring in tropical and subtropical regions across all continents [1]. The virus circulates as four serotypes (DENV-1 to DENV-4) [2] and is transmitted primarily by Aedes aegypti, with other Aedes species, chiefly Aedes albopictus, playing a secondary role [1]. About half of the world's population is at risk, and annual infections range from 100 to 400 million, including a modeled 390 million per year, of which 96 million are clinically apparent [1,3]. Asia bears the greatest burden (about 75%), followed by Latin America and Africa [4]. In 2024 alone, more than 14.6 million cases were reported to WHO, over 13 million of them from the Americas, but reported numbers underestimate the true burden [1]. Climate change, shifting vector distribution, urbanization, and population movement contribute to its spread [1].
The clinical picture varies widely. Most infections cause no symptoms or a self-limited febrile illness [1,4,5]. Some patients develop dengue with warning signs, such as abdominal pain or tenderness, persistent vomiting, clinical fluid accumulation, mucosal bleeding, lethargy, hepatomegaly, or a rapid fall in platelet count accompanied by a rising hematocrit [1,4,5]. A minority progress to severe dengue, defined by severe plasma leakage, severe bleeding, or severe organ involvement [1,4,5,6]. This three-tier scheme replaced the earlier division into dengue fever, dengue hemorrhagic fever, and dengue shock syndrome, yet many genetic studies still use the older clinical categories, complicating literature analysis [2].
The most robustly established risk factor for severe dengue is secondary infection with a heterologous serotype, which significantly increases the likelihood of severe clinical manifestations [1]. In such cases, heterotypic antibodies elicited by prior infection may enhance viral entry into Fc receptor–bearing cells, a process known as antibody-dependent enhancement [6]. Additional determinants include viral serotype, viral load, and viral genotype, as well as host-related factors such as age and comorbidities—including diabetes mellitus and chronic kidney disease [6,7,8,9]. Investigations have also addressed the roles of blood group, ethnicity, and nutritional status in modulating disease risk [10]. However, these variables do not fully account for the divergent clinical trajectories observed among individuals with similar exposure histories. This is underscored by the fact that over 99% of secondary infections remain clinically mild [4,5]. Geographic variation is also apparent: severe manifestations are more prevalent in Southeast Asia, whereas in Latin America the clinical presentation is typically less severe and predominantly affects adults [4,5]. Intra-regional ancestry differences are also relevant, as African genetic ancestry has been associated with protection against severe dengue in Colombian populations [11].
This review systematically examines host genetic susceptibility to dengue, with particular attention to the progression from mild disease to warning signs and severe clinical outcomes. It synthesizes current findings regarding HLA alleles, haplotypes, and polymorphisms in immune-related genes, providing comparative analyses across diverse endemic regions. It also provides a general overview of new approaches and techniques. The review also highlights methodological limitations that constrain the interpretation of existing genetic association studies. Thus, the review is narrative and not analytic.

2. Materials and Methods

This narrative review provides a comprehensive, methodologically informed synthesis of human genetic association studies in dengue. Although this review is not a formal systematic review or meta-analysis was performed, a close attention to study heterogeneity and limited sample sizes, which we recognized as significant analytical limitations. Studies were included based on rigorous criteria: well-defined clinical phenotypes and robust genetic methodologies. Given the marked variability in participant characteristics, genetic markers, case definitions, and analytical methods, the principal objective was to integrate and interpret findings across diverse populations. Unpublished sources were excluded.
A systematic review protocol was not employed, nor were effect estimates pooled. The heterogeneity of the studies and the sample sizes in several reports limited a formal, in-depth statistical analysis. We searched PubMed, Scopus, and Web of Science, along with the Latin American regional databases SciELO and LILACS, from each database's inception to 23 September 2026. Search terms combined dengue with terms for host genetics, including genetic susceptibility, polymorphism, HLA, haplotype, candidate gene, and genome-wide association. The reference lists of relevant articles and reviews were also screened to identify additional studies. Because some Latin American literature is published in journals not indexed in the databases above, we also searched the tables of contents of selected regional journals by hand. We discarded duplicate reports based on the title, authors, sample size, and analysis.
Original human studies investigating germline variants—including HLA alleles or haplotypes, candidate gene polymorphisms, and genome-wide markers—in relation to dengue susceptibility or clinical severity in patients with laboratory-confirmed infection and an appropriately defined comparison group were included. Special emphasis was placed on adherence to the World Health Organization (WHO) clinical criteria for dengue case definitions, given their central importance for methodological rigor and comparability across studies. [1]. We excluded animal and in vitro studies, case reports, viral genetic research without host genotyping, conference abstracts, and preprints because our aim was humans and the reports had to include well-defined methodological assays.
For each study, we systematically extracted data on the population, sample size, case definition, infecting serotype, genetic variant, effect estimates, and statistical significance after correction or replication. Findings were organized by gene family and clinical category for qualitative synthesis. Formal risk-of-bias assessment was not performed due to heterogeneity in study designs and the narrative nature of this review.
The 2009 WHO classification system delineates dengue into three clinical categories: dengue without warning signs, dengue with warning signs, and severe dengue [5]. This system replaced the 1997 classification, which was based on dengue fever, dengue hemorrhagic fever, and dengue shock syndrome. Notably, most genetic association studies were conducted before the revised WHO guidelines and therefore used the earlier clinical categories. For example, the Venezuelan [11] and Brazilian [12] HLA cohort studies adopted the 1997 framework. To maintain methodological consistency with primary sources, a major review of the field retained the 1997 categories in its analysis [2]. Similarly, a recent meta-analysis examining HLA-A*24 and HLA-B*44 associations restricted its inclusion criteria to studies using the 1997 classification, thereby excluding those using the 2009 scheme [13].
Accurate definition of clinical phenotypes is essential in dengue genetic association studies. Studies vary in their comparators, contrasting healthy controls, asymptomatic, mild, or severe cases, and increasingly distinguishing dengue shock syndrome per the 2009 WHO guidelines [1]. Because genetic associations are context-dependent, this review specifies the reference group for each study cited.

3. Host Genetic Factors

Host genetic factors affect dengue risk, but most associations remain unconfirmed [1,4,5,14,15,16,17]. The geographic distribution of this research is uneven. A 2025 meta-analysis of HLA studies included 19 case-control studies worldwide and identified several key associations in Southeast Asian populations [17]. Although the Americas accounted for most of the world's cases in 2024 [1,18,19], the literature contains few reports [18,19]. The genetic data from African populations are scarce (16). A 2025 meta-analysis found no HLA case-control study from tropical Africa [17]. This information gap is critical because populations in Latin America carry a mixture of Amerindian, European, and African ancestry, so their HLA and immune gene diversity may differ from that of Asian cohorts. In Venezuela's central urban population, for example, ancestry has been estimated at roughly 60% European, 24% Amerindian, and 16% African [20]. This heterogeneity includes differences among the places in Africa where the populations were introduced, e.g., Western or Eastern Africa, with distinct Amerindian and Caucasian populations, resulting in admixed populations that are difficult to define precisely.

3.1. HLA Class I Alleles

As described in Table 1, HLA molecules present viral peptides to T cells, influencing dengue susceptibility. HLA-A*24 is the most consistently associated allele, especially in Asian populations, with an increased risk of severe dengue, as multiple studies have linked it to this outcome. A*33 appears protective in Southeast Asia. Most associations are region-specific and often do not replicate across populations [16,21,22,23,24,25]. Evidence for A*24 in non-Asian groups is limited.
Other HLA class I associations exhibit considerable heterogeneity, with allele-disease relationships varying across viral subtypes and serotypes. In a Thai study, no HLA-A or -B association was seen in primary infection [25]. For secondary infections, A*0203 was more common in dengue fever than in controls and less common in hemorrhagic fever, both findings holding after correction. A*0207 was associated with hemorrhagic fever for certain serotypes but was not significant after correction. A meta-analysis found A*02 associated with dengue fever mainly in Southeast Asia, with high heterogeneity [16]. A*03 was reported as a risk allele for hemorrhagic fever based on one Thai study but not regionally. A*33 appeared protective in some analyses, though results varied, with one Caribbean study showing the opposite [25]. In Venezuela [11], A*03 was absent in patients with hemorrhagic fever, but this did not hold after strict statistical correction [11]. A Malaysian study found A*03 to be less frequent in hemorrhagic fever than in controls, but the difference was not significant after correction [24]. Overall, the direction of A*03’s effect varies across populations, even within Southeast Asia.
The direction of the HLA-B*44 association changes with context. In a cohort from Recife, Brazil, infected with DENV-3, hemorrhagic fever was more frequent than dengue fever (15.8% versus 8.5%; OR 2.03, 95% CI 0.97 to 4.24; P = 0.047), without correction for multiple testing [13]. In the same Thai cohort, B*44 was less frequent in secondary hemorrhagic fever than in controls, alongside B*62, B*76, and B*77; none of these were corrected for multiple comparisons [13,25]. The 2025 meta-analysis found B*44 protective against hemorrhagic fever (OR 0.60; 95% CI 0.44 to 0.82) but not against dengue fever or symptomatic dengue overall [16]. Two Thai studies showed protection (OR 0.65; 95% CI 0.49 to 0.87) [25,26], whereas Latin America showed a risk effect (OR 1.37; 95% CI 1.02 to 1.85) driven mainly by the southern Brazilian study [12,16]. A dedicated meta-analysis of A*24 and B*44 concluded that the two alleles have opposing effects on hemorrhagic fever [13].
In the Venezuelan case-control study, B*57 was more frequent in patients with dengue fever than in controls (7.0% versus 1.6%; OR 4.68), and B*40 was more frequent in patients with hemorrhagic manifestations than in controls (17.9% versus 8.7%; OR 2.29). B*15 and B*49 were less frequent in patients overall [11]. The study included 77 patients and 127 controls, and all of the class I differences were no longer significant after Bonferroni correction [11]. The B*15 result is consistent with the Cuban data, in which B*15 and A*31 were associated with symptomatic dengue in patients with DENV-2 [2,27]. B*13 was linked to resistance in Thai patients with shock (2). In a Malaysian series, it went the other way: it was more frequent in Malay patients with hemorrhagic fever (16% versus 3%; P = 0.049, not significant after correction) and absent in Chinese patients with the same diagnosis [24].

3.2. Class II Alleles

Class II alleles generally showed protective effects, but findings varied by population. DRB1*0901 conferred protection against shock in Vietnamese patients, particularly with DENV-2 [22]. DRB1*04 was protective in Mexican and Cuban patients [12,27,28] but not in a Brazilian cohort. DRB1*15 was the only association in the Venezuelan series to remain significant after correction, and it was also more frequent in Brazilian patients, though not after correction. DQ1 was linked to dengue fever in southern Brazil [29,30]. DRB1*11 was associated with severe dengue in some studies, but the results were inconsistent and often became non-significant after adjustment. Other alleles, including DRB1*03 and DRB1*09, were sometimes associated with lower risk, but these findings varied by region and did not always reach statistical significance [29,30]. In Burkina Faso, DRB1*11 and DRB1*03 were less frequent among patients, but the differences were not statistically significant after correction [31,32]. Overall, the evidence for class II allele protection is mixed and often limited by small sample sizes and inconsistent results between regions.
Two alleles in the Brazilian cohort were associated with cross-serotype immunity rather than protection against severity. B*07 and DRB1*13 were less frequent in secondary than in primary DENV-3 infections (ORs of about 0.50 for each, one-sided tests without correction for multiple testing), which the authors interpreted as evidence of cross-protective T cell responses [12]. The interpretation is not straightforward. In 10 HLA-B*07-positive Thai children, T cells specific for a conserved NS3 epitope were detectable in 9, at a median frequency of about 1 in 15,000 circulating cells, and this frequency was higher in children with hemorrhagic fever than in those with dengue fever (P = 0.03), a difference that held after excluding the one child with primary infection (P = 0.046) [32].
Table 1 summarizes the genetic associations identified in the reviewed studies, along with the specific populations in which these associations were observed.
Table 1. Selected HLA associations with dengue outcomes across populations.
Table 1. Selected HLA associations with dengue outcomes across populations.
Gene Population Observation Ref
A*24 (codon 70 histidine) Vietnam, two sites Risk of DHF and DSS [21,22]
A*24 Southeast Asia (meta-analysis); Caribbean, one small study Risk of DHF and symptomatic dengue; no association with DF [16]
A*0203, A*0207 Thailand, secondary infection A*0203 with DF; A*0207 with DHF or DSS [25]
A*03 Southeast Asia (meta-analysis); Malaysia; Venezuela Risk of DHF (meta-analysis, driven by one Thai study); less frequent in DHF, not significant after correction (Malaysia, Venezuela) [11,16,24]
A*33 Southeast Asia (meta-analyses) Protection against DHF and symptomatic dengue [16,23]
B*44 Brazil, DENV-3 Risk of DHF (nominal, no correction) [12]
B*44, B*62, B*76, B*77 Thailand, secondary infection Lower frequency in DHF than in controls (uncorrected) [12,25]
B*51, B*52 Thailand, secondary infection B*51 with DHF; B*52 with DF in DEN-1/DEN-2 (uncorrected) [25]
B*15 DENV-2; Mexico, Venezuela Risk of symptomatic dengue (Mexico); lower frequency in patients (Venezuela, nominal) [11,28]
B*40, B*57 Venezuela B*40 with hemorrhagic manifestations; B*57 with DF (nominal) [11]
DRB1*0901 Vietnam Protection against DSS [22]
DRB1*04 Mexico, Cuba, Brazil Protection in Mexico and Cuba; no effect in Brazil [12,27,28]
DRB1*15 Venezuela; southern Brazil (DENV-3) Susceptibility to dengue (significant after correction in Venezuela; nominal in Brazil) [11,30]
DRB1*03 Venezuela; meta-analysis; Burkina Faso Lower frequency in patients (Venezuela, nominal); lower risk of severe dengue (meta-analysis); lower odds of dengue (Burkina Faso) [11,23,32]
DRB1*11 Meta-analysis; southern Brazil (DENV-3); Burkina Faso Risk of severe dengue versus DF (meta-analysis of two studies); resistance to dengue (Brazil, not significant after correction); no association (Burkina Faso) [23,30,31]
B*07, DRB1*13 Brazil, DENV-3 Lower frequency in secondary infection [12]
TNF -308 (rs1800629) Venezuela; Cuba; Southeast Asia A allele with hemorrhagic manifestations (Venezuela) and shock (Cuba); no association in larger Southeast Asian cohorts Not significant after correction in Venezuela; pooled meta-analyses null [2,34,35]
TNF -308 with IL10 -1082 AA Venezuela High TNF and low IL-10 profile more frequent in DHF than in controls (OR 19.5) or DF (OR 17.4) Very wide CI; not significant after correction [34]
TNF rs1799964 Colombia, children C-allele carriers less frequent among patients (aOR 0.51) FDR 0.0017 [36,37]
Table legend: DF, dengue fever; DHF, dengue hemorrhagic fever; DSS, dengue shock syndrome; DENV, dengue virus.

3.3. Haplotypes

Haplotype-level data are scarcer than allele-level data. Among 435 ethnic Thais, a TNF haplotype marked by the -238A substitution was more frequent in secondary hemorrhagic fever (15.2%) than in secondary dengue fever (4.1%; OR 4.13; 95% CI 1.59 to 11.17), a difference that remained significant after multiple-testing correction [26]. In most carriers, the same variant was linked to a specific LTA haplotype that correlated with detectable LTA and TNF production during the acute phase [26]. In contrast, LTA variants alone showed no association with any patient group. Two extended haplotypes combining these TNF and LTA variants were found only in secondary hemorrhagic fever (7.8%) and in controls (2.1%), never in secondary dengue fever, and in the hemorrhagic fever group they co-occurred with HLA-B*48, a serotype otherwise rare in Southeast Asia, as well as with B*57 and DPB1*0501. Stratifying by infecting serotype revealed no further association [2,26]. In the Venezuelan series, the authors observed that DRB1*03 was not enriched among carriers of the TNF -308 A allele and attributed this to the genetic heterogeneity of the population [11].

3.4. Cytokine Genes

Although TNF has been widely studied, most research—including meta-analyses—found no consistent association between TNF variants and severe dengue overall [34,35,36,37,38]. The A allele of the TNF-308 promoter showed possible links with severe disease in Venezuela and Cuba, but not in Southeast Asia, and these results often lost significance after correction [34,35]. Other TNF and IL-10 gene combinations also showed inconsistent results or wide confidence intervals. A large meta-analysis and a Brazilian study both found no significant associations [38]. In Colombia, a different TNF variant (rs1799964) was less common in patients than in controls [39], whereas the opposite was reported in India [40]. Overall, TNF's role in dengue severity remains unclear and likely varies by population.
A systematic review of Latin American case-control studies included 26 articles: 12 from Brazil, 7 from Mexico, 5 from Cuba, and 2 from Venezuela. The abstract reports 16 articles linking polymorphisms to a higher risk of severe dengue and 16 to protection, so some articles reported both. TNF was the most studied gene, in eight studies, and the findings were inconsistent, which the authors attributed to differences in populations, sample sizes, and genotyping methods [9]. In a Colombian sample of 226 patients, the GGT and GAC combinations of rs1800750 (TNFA), rs2069843 (IL6) and rs2069705 (IFNG) were associated with hemorrhagic fever, with and without adjustment for ancestral genetic component [37]. The A allele of rs2069843 alone was associated with hemorrhagic fever in Afro-Colombians and, after adjustment for ancestry, in the full sample. Carriers of the AGC combination had IL-6 levels that were 58.03 pg/mL higher than those of GGC carriers, independent of European, Amerindian, and African ancestry proportions [37]. rs1800750 is a different TNFA position from the -308 variant (rs1800629).
Two regulatory cytokine genes have also been studied. In Taiwanese patients, TGFB1 -509 CC was about twice as frequent in hemorrhagic fever as in dengue fever, and its combination with CTLA4 +49 G further increased the risk. It was associated with a higher DENV-2 viral load. In Cuba, the G allele at TGFB1 codon 25 was protective [2].

3.5. Other Genes Involved in Immune Response

The FCGR2A R/R131 genotype was one of the first non-HLA genetic associations identified in dengue [41,42,43,44,45]. In Vietnamese children, the R/R genotype was less common among severe cases, suggesting a protective effect, though the association was borderline statistically significant [42]. In Cuban adults, R/R was also protective against hemorrhagic fever, while the H/H genotype was associated with both dengue fever and hemorrhagic fever [42,43]. However, in a Mexican cohort, the histidine (H) allele was protective, showing the opposite direction [9]. These conflicting results may reflect differences in population genetics, serotype, infection history, or case definitions. The role of FCGR2A in antibody-dependent enhancement is plausible but not definitively proven, and its effects may differ from those observed in other viral infections, such as SARS-CoV-2.
The CD209 (DC-SIGN) promoter variant -336 G was studied in 606 people with dengue and 696 controls across three Thai hospitals [45]. Carriers of the G allele were sporadic in dengue fever (4.7%) compared with hemorrhagic fever (22.4%; OR for hemorrhagic fever versus dengue fever 5.84; 95% CI 2.77 to 12.31) and with controls (19.5%; OR for protection against dengue fever 4.90; both P values below 10⁻⁶), a pattern replicated in all three cohorts [45]. The frequency of hemorrhagic fever did not differ from that of controls. Reduced promoter activity was proposed as the mechanism [2,45]. In Brazilian populations, studies have yielded contrasting results. The association was not found in one study [2], whereas it was positive in another [46], suggesting diverse population admixture within the same country. Results elsewhere diverge. In Taiwan, the G allele was linked to hemorrhagic fever [47]. In a Mexican cohort, it was rare (5.4%) and only marginally associated with symptomatic infection (OR 2.3; 95% CI 0.91 to 6.1), in a study with 56% power [44]. Studies in Western India [48], in 918 Thai children comparing hemorrhagic fever with dengue fever (OR 0.85; 95% CI 0.63 to 1.15) [49], and in Burkina Faso [50] found no association. A meta-analysis of nine papers reported that G carriers had a higher risk of severe dengue in Asians (dominant model, OR 1.86; 95% CI 1.01 to 3.45) but a lower risk in South-Central Americans (GG versus GA/AA, OR 0.27; 95% CI 0.10 to 0.70). The overall pooled estimates were not robust [50]. In Brazilian children admitted with shock, the GG genotype was protective (OR 0.12; 95% CI 0.01 to 0.9), but this was based on one GG carrier among 85 genotyped cases versus 28 among 322 controls [51]. The same study pooled published data and found the G allele associated with severe dengue in Asians (allelic OR 2.77; 95% CI 1.65 to 4.67) and with protection in Brazilians (OR 0.66; P = 0.013) [51].
Antigen processing at the platelet surface is also critical in dengue. In South Indian patients, TAP1 333 Ile/Val was associated with hemorrhagic fever, and HPA-1 1a/1b heterozygosity with shock rather than hemorrhagic fever without shock (OR 4.75). The authors linked both findings to viral peptide selection and to a cross-reactive immune response against a platelet antigen [2,52].
Mannose-binding lectin (MBL2), part of the complement lectin pathway, has also been examined in relation to platelet count. In 110 Brazilian patients infected with DENV-3, MBL2 genotype frequencies did not differ from those of healthy controls, so the gene was not associated with dengue infection [53,54]. Among patients, however, the AA genotype, which produces normal amounts of the protein, was more common among those who developed thrombocytopenia than among those who did not, after adjusting for age (OR 2.32; 90% CI 1.13 to 4.79; P = 0.056). This is the opposite of what a simple deficiency model would predict, since low-producer genotypes are usually associated with worse outcomes in other infections [54]. A similar finding was reported in a study of a Vietnamese population [55].
The C-type lectin CLEC5A offers a functional link back to the cytokine signals discussed above. In the same Brazilian study, the rs1285933 TT genotype was more frequent in children with shock than in matched controls (OR 2.25; 95% CI 1.07 to 4.87) [51]. Carriers of the T allele had higher TNF levels on days 5 to 7 of illness in a functional sample of 38 patients. The association was borderline when only IgG-positive controls were used (OR 2.03; P = 0.12), and the authors consider it preliminary and requiring replication [51].
In a Vietnamese cohort study investigating FCGR2A, the genotype frequencies at the vitamin D receptor (VDR) locus 352 showed no statistically significant difference between 327 cases and 247 controls (P = 0.154) [51]. However, a trend analysis of allele frequencies across two shock severity grades indicated that the T allele was less prevalent in individuals with the more severe grade (P = 0.033), which the authors interpreted as suggestive of a potential protective effect (2,38). Additional genes assessed in the same study, including mannose-binding lectin, IL-4, and IL-1RA, were not found to be associated [41]. The association observed for VDR has not been replicated in the sources reviewed herein. Table 2 provides a summary of the non-HLA genetic associations discussed in this and subsequent sections, alongside their statistical significance.
The roles of KIR are still difficult to interpret due to de limitations of studies [58,59,60]. Other studies involving other genes need to be confirmed, except for the strong association with MICB [15,33,36,61,62]. A high correlation has been identified in GWAS and should be validated by upcoming studies.
Table 2 summarizes the genes involved in the process and lists suitable candidates. Some of the genes have been validated in a specific population, while others have been suggested by genetic analysis, such as OAS1 (2'-5'-oligoadenylate synthetase 1), OAS3 (2'-5'-oligoadenylate synthetase 3), and SNP rs2285933, which belong to the IFN signallome but have not been directly validated in individuals with disease. In essence, the decreased or absent IFN type I and III responses are crucial for the lack of protection against infection, severity, and chronicity in most viral diseases [69].
Table 2. Other gene associations with dengue outcomes across populations.
Table 2. Other gene associations with dengue outcomes across populations.
Gene Population Observations Ref
TNFA rs1800750, IL6 rs2069843, IFNγ rs2069705 Colombia GGT and GAC combinations with DHF; A allele of rs2069843 with DHF after ancestry adjustment Adjusted for ancestry; single cohort [37]
TGFβ1 -509 CC; TGFβ1 codon 25 G Taiwan; Cuba -509 CC about twice as frequent in DHF as in DF, risk increased with CTLA4 +49 G; codon 25 G protective in Cuba Uncorrected; not replicated [2]
FCGR2A R/R131 Vietnam; Cuba; Mexico Protective against shock (Vietnam) and against DHF (Cuba); histidine allele protective against symptomatic infection in Mexico, the opposite direction One-tailed significance in Vietnam, CI crosses 1; direction reverses in Mexico [2,41,42,43,44]
CD209 (DC-SIGN) -336 A/G Thailand; Taiwan; Mexico; Brazil; India; Burkina Faso G allele protective against DF in three Thai cohorts; risk of DHF in Taiwan; GG protective in Brazilian shock cases; no association in India, Burkina Faso, or a second Thai cohort Replicated within Thailand; direction reverses between Asia and South-Central America [2,44,45,46,47,48,52]
TAP1 333 Ile/Val; HPA-1 1a/1b South India TAP1 with DHF; HPA-1 heterozygosity with shock (OR 4.75) Single cohort; not replicated [2,53]
MBL2 AA Brazil, DENV-3
Vietnam		 No association with infection in Brazil. Association in Vietnam. AA more frequent among patients with thrombocytopenia. P = 0.056; opposite of a deficiency model [54,55,56,57]
CLEC5A rs1285933 TT Brazil, children with shock More frequent in shock than in matched controls (OR 2.25); T allele with higher TNF levels Borderline with IgG-positive controls; authors call it preliminary [51]
VDR position 352 Vietnam No difference in genotype frequencies; trend toward lower t allele with greater severity Trend test P = 0.033; not replicated [2,41]
KIR2DL2, KIR2DL5A, KIR2DL5B; KIR3DL3, KIR2DS5 Burkina Faso, pilot study Three inhibitory receptor genes more frequent in patients (OR 7.32 to 15.0); KIR3DL3 and KIR2DS5 less frequent Small sample (50 patients); DHF not recorded [58]
KIR2DS5, KIR2DL5, KIR AA genotype Southern Brazil KIR2DS5 and KIR2DL5 more frequent in patients; AA genotype protective (OR 0.46); opposite direction to Burkina Faso for two genes Single cohort; conflicts with 54 [59]
KIR3DL1, KIR3DS1/3DS1 Western India KIR3DL1 more frequent in DF than controls (OR 4.1); KIR3DS1/3DS1 less frequent Neither survived correction; no DHF discrimination [60]
Toll receptor
3, 4, 7, 8, 9		 India, Mexico, Colombia, and Indonesia TLR3 rs3775291 and rs3775290, TLR4 rs4986790 and rs4986791, and TLR7 rs179008 and rs3853839 correlate with dengue severity Meta analysis [61]
Complement receptor type 1 Vietnam CR1 minor allele rs6691117G associated with infection and severity Values of ELISA reveal association of complement receptor 2 with platelets [62]
MICB rs3132468 Vietnam (GWAS and follow-up); Cuba; Colombia; meta-analysis Risk of shock (per-allele OR 1.34) and of dengue without shock (OR 1.15); GG genotype with symptomatic dengue in Colombia (aOR 3.01) Genome-wide significant and replicated; causal gene within MHC not defined [15,33,36,63,64,65]]
PLCE1 rs3765524, rs3740360, rs2274223 Vietnam (GWAS and follow-up); Colombia; meta-analyses Protective against shock (rs3765524 OR 0.80); CT genotype with symptomatic dengue in Colombia (aOR 1.78), direction consistent Genome-wide significant and replicated; functional validation pending [15,33,36,63,65,66]
JAK1 rs11208534, rs2780831, rs310196 Brazil (pathway study); Colombia Eleven of 58 nominal markers in JAK1, clustered toward the 5′ end, with DHF; rs11208534 with severity in Huila only Nominal P < 0.05, no genome-wide threshold; department-specific in Colombia [2,14,36]
BAK1 rs5745568 Thailand, 918 children Recessive association with DHF (adjusted OR 1.29), independent of CD209 Single cohort; causal variant possibly in linkage disequilibrium [49]
NOD1, RIPK2, IKBKE Colombia NOD1 and RIPK2 variants with risk; IKBKE haplotypes with resistance; IKBKE rs1059704 reverses direction between departments FDR-corrected; several signals present in one department only [36]
OSBPL10, RXRA Cuba, admixture mapping Lower African ancestry in DHF; both genes converge on the LXR/RXR pathway; OSBPL10 knockdown reduced DENV-2 replication Pattern held in Havana but not in Guantánamo; functional support in vitro [17,66]
Thrombopoietin receptor Bangladesh Genetic polymorphism of thrombopoietin receptor and GATA1 Response to eltrombopag (treatment for thrombocytopenia) [67]
OAS1, OAS3 rs2285933 Meta-analysis weighted by worldwide allele frequency OAS3 rs2285933-G protective against shock (OR 0.55) Not examined in any primary study reviewed here [65,68]
Table legend: DF, dengue fever; DHF, dengue hemorrhagic fever; DENV, dengue virus; GWA.

4. Genetic Analysis in Africa and Latin America

Table 1 and Table 2 present the relevant information for the topic. The Tables show several specific studies across different populations, with the most informative coming from Asian populations. A logical limitation as compared with African and Latin American cohorts.
Few studies have examined host genes in relation to dengue in Africa. Recent reviews found no African study linking viral genotype or serotype to individual disease severity [71,72]. A small pilot study found that certain inhibitory KIR genes were more common in patients, while protective KIR genes were less frequent, though sample sizes were modest [58]. In southern Brazil, the same KIR genes showed the opposite pattern [59]. Other studies, including those from Western India, reported inconsistent results for KIR genes, with no clear association with severe disease after correction [60]. Furthermore, studies of HLA class II alleles in Burkina Faso found only DRB1*03 with a possible protective effect [32]. No association was seen for DC-SIGN variants in Africa or for HLA-DRB1*11 and DRB1*12 [77]. Overall, the evidence from African and related populations is limited, inconsistent, and based on small sample sizes [72,76].
Findings from Latin America are from Venezuela, Brazil, Mexico, Cuba, and Colombia, mostly from populations of mixed Amerindian, European, and African ancestry. A systematic review of 26 Latin American case-control studies counted contributions by country: 12 from Brazil, 7 from Mexico, 5 from Cuba, and 2 from Venezuela; more recent Colombian studies are not included in that count [9]. One association does replicate within the region. DRB1*15 was linked to dengue in the Venezuelan cohort and, independently, in a southern Brazilian cohort infected with DENV-3, in both cases surviving correction for multiple comparisons [11,30]. Most other findings do not travel even within Latin America. TNF -308A was a risk allele for hemorrhagic manifestations in Venezuela [34] but was not associated with shock in the Brazilian cohort or in a pooled Latin American analysis [35,51]. DRB1*04 was protective in Mexican and Cuban patients but had no effect in the Brazilian DENV-3 cohort [12,27,28]. FCGR2A followed the same pattern in reverse: the H/H genotype was a risk factor in two Cuban studies (39,40), while the histidine allele was protective in a Mexican cohort [44].
No genome-wide association study has been carried out in an admixed Latin American population. The two loci with genome-wide support, MICB and PLCE1, come from Vietnam and were tested in a candidate-gene manner, not searched genome-wide, in the one Colombian study that examined them [15,36]. Given the ancestral diversity within Latin American populations, this gap may matter as much as the one already noted for Africa [17].
Genetic information clusters in different countries — Brazil, Colombia, India, Burkina Faso, for example — can only give partial information on local populations. More countries should be involved in the process. Interestingly, information on HLA for transplant programs can serve as a basic tool in countries with less favorable economic conditions for sponsoring large-scale population sequencing studies.

5. Genes and Cell Targets That Require Further Exploration

In recent years, it has become clear that gene-level analyses and GWAS only provide partial insights into susceptibility and protection, and that more is needed at the cellular level to understand dengue viral infection and its severity. Latif and coworkers [78] have identified, using in silico approaches, several key transcription factors involved in infection, viral replication, and chronicity that are new to the analysis. They identified the roles of the transcription factors FOXC1, GATA2, RELA, TP53, and PPARG [78]. Moreover, PTEN and BIRC5 could inhibit the host's IFN responses, thereby facilitating viral infection [78]. This study suggests that the genetics of IFN type I and III signaling pathways should be further analyzed in dengue infection.
Josyula et al. [79] analyzed gene signatures in dengue infection and identified seven hub genes, PIK3R1, GATA3, ZFPM, SKAP1 (involved in hemostasis, platelet activation, aggregation, and production), TP63, ZBTB20, and ZEB2 (associated with abnormal hard palate morphology), for dengue diagnosis. Even though these genes do not directly relate to the targets identified by Latif, it is clear that a more complex array of genes and proteins are involved in dengue infection and could be critical in post-dengue syndrome.
Datta and Gosh [80] applied an interesting rationale. They analyzed different dengue types and genetics in the Indian population. Ten hubs were defined in each condition: DF, DHF, and DSS. It became clear that the hubs represented most of the intermediates involved in IFN signaling. Two of the most critical in dengue infection are IFIT1, an innate immune sensor and antiviral effector that restricts viral infection by identifying foreign viral RNA and blocking its translation, and interferon-stimulated gene 15 (ISG15) is a ubiquitin-like modifier protein induced by type I interferons that acts both as an intracellular protein tag (ISGylation) and an extracellular cytokine to fight infections and regulate immune responses. For DHF, other genes have been related: 1) FXR2, FMR1 Autosomal Homolog 2, a protein-coding gene belonging to the fragile X-related family; 2) the E3 ubiquitin-protein ligaseZNF598; 3) SMG1, a protein-coding gene that encodes an atypical serine/threonine protein kinase belonging to the phosphatidylinositol 3-kinase-related kinase family. SMG1; 4) Pumilio RNA-Binding Family Member 2 (PUM2); it encodes a sequence-specific RNA-binding protein that acts as a post-transcriptional regulator of genes; 5) Replication initiator 1 (REPIN1); it enables RNA-binding activity as a replication factor; 6) parafibromin (CDC73), which regulates gene transcription, RNA processing, and histone modifications. 7) CDK19 is a serine-threonine kinase that regulates RNA polymerase II; 8) CACTIN is a nuclear scaffold protein involved in pre-mRNA splicing; PAGR1; and 9) RPS6KB2 is a ribosomal protein S6 kinase beta-2, a serine/threonine kinase that controls protein synthesis and cell proliferation. DSS: 1) Phosphatidylinositol 3-Kinase Catalytic Subunit Type 3, PIK3C3, is a class III lipid kinase; 2) alpha subunit of hypoxia-inducible factor 1, HIF1A, a master transcription factor that coordinates how cells adapt to low oxygen levels; 3) SBF1 regulates membrane dynamics and endosomal trafficking; 4) FZR1 is a crucial substrate-specific activator and adapter for the anaphase-promoting complex/cyclosome (APC/C) E3 ubiquitin ligase complex.; 5) ROCK1 is a Rho-associated protein kinase 1, a crucial serine/threonine protein kinase activated by the small GTPase RHOA; 6) DICER1 is an enzyme that builds microRNAs; 7) dynamin-related protein 1, DNM1L, controls how cells divide and controls mitochondrial energy production; 8) STK11 is a serine/threonine protein kinase that acts as a major tumor suppressor by regulating cell metabolism, polarity, and growth; 9) ABL1 a non-receptor tyrosine kinase protein; and 10) BRD1 is a human protein-coding gene that acts as an epigenetic regulator and a core component of histone acetyltransferase (HAT) complexes. Although several genes have been analyzed in viral infections [81], some of the candidates identified by Datta and Ghosh have not been linked to viral infection or the innate immune response. Future research should be directed to validate these targets.
Khare et al. [82] published a preliminary study analyzing the genetics of T cell receptor αβ and γδ in 112 dengue patients. Although no major conclusions can be drawn from this report, future studies should explore this point further, as the role of innate lymphoid cell populations in dengue infection remains poorly understood [6]. As recently reviewed, there are several controversies regarding severe dengue infection that warrant further analysis [83].
These new approaches and models require clinical validation and underscore the need for new, well-defined human population studies involving genetics and pharmacogenetics. Research on immune responses, including antigen presentation, humoral immunity, innate immunity, and adaptive immunity, is urgently needed.

6. Discussion

Genetic associations remain inconsistent across both mechanistic pathways and populations as shown in Table 1 and Table 2. Only three findings are supported by more than one independent study: HLA-A*24 in Vietnamese cohorts; FCGR2A R/R131 in Vietnamese and Cuban patients (with conflicting evidence from Mexico); and MICB and PLCE1, replicated in Vietnam and observed again in Colombian children. These replicated findings are largely limited to Southeast Asia, Cuba, and Colombia. Numerous genetic associations exhibit substantial heterogeneity and often vary across cohorts and population contexts. For example, HLA-B*44 is associated with increased risk in Brazilian DENV-3 cases but is less common among Thai patients with secondary hemorrhagic fever. HLA-B*35 is significantly less frequent among Mexican dengue patients than controls, an association that persists after correction. HLA-B*15 is linked to symptomatic dengue in Cuba but is less frequent in Venezuela. DRB1*04 confers protection in Mexican and Cuban cohorts but has no detectable effect in the Brazilian cohort. DQB1*0302 and DQB1*0202 frequencies also vary by clinical manifestation, yet their associations do not withstand multiple-testing correction. The TNF -308A allele appears to confer risk in South America but not in Southeast Asia, with meta-analyses showing no overall effect. Similarly, the DC-SIGN -336G allele is a risk factor in Asian populations and appears protective in South-Central Americans, yet some large Thai cohorts report no association. The FCGR2A R/R131 genotype is protective in Vietnam and Cuba but associated with risk in Mexico. DRB1*11 is inconsistently associated with disease severity across studies and regions, while DRB1*03 appears protective in some populations but not in others. Although several loci (including MICB, TNF, CD209, FCGR2A, TPSAB1, CLEC5A, IL10, and PLCE1) have been identified as replicated across populations, the evidence supporting their roles varies by ancestry, geography, and study design.
These inconsistencies in the literature have given rise to three principal hypotheses regarding population-specific effects, serotype and infection history, and the nature of the immune response, each of which warrants further empirical investigation.
The first is serotype and infection history. HLA molecules present different peptides, and some epitopes are more conserved across serotypes than others [84,85] and are critical in mapping the immune response. Most associations described in dengue appeared only in secondary infections and varied by infecting serotype, suggesting that the reported results may overstate the conclusions drawn from a single analysis.
The second is population structure. The susceptibility and severity of infection vary between populations. The risk of conducting meta-analyses with heterogeneous reports has been highlighted in several studies [13,17,23,33,35,38,51,52,65]; few conclusions can be drawn from these studies. It is unclear whether, in the Latin American admixed population, Caucasian genes are associated with susceptibility and African genes with resistance, given that gene segregation across countries varies with the origin of the Caucasian and African populations. In consequence, it is risky to conclude that African ancestry is protective.
The third is the role of type I and type III IFNs and the immune cell response in viral infection. The data analysis discussed in point 8 of this manuscript is critical for properly defining the genes and proteins involved in dengue infection and severity. There are still many unresolved issues that need to be addressed.
Future research should adopt the 2009 World Health Organization classification and systematically document serotype and primary versus secondary infection status to ensure phenotype comparability across cohorts [2,21]. Functional validation of associations, alongside adequately powered genome-wide analyses, are needed in diverse, well-defined populations. If these associations prove robust, they may inform preventive and immunotherapeutic strategies, including vaccine design, and help identify individuals at heightened risk for disease progression [2]. Comparative analyses with SARS-CoV-2, which shares key immunopathogenic mechanisms, may further elucidate host genetic determinants relevant to both infections [6]. Ongoing dengue vaccine trials offer valuable opportunities for genetic analyses to evaluate immune response efficacy and disease severity. Additionally, comprehensive assessment of viral coinfections is essential, particularly in regions with substantial prior exposure to other flaviviruses, as such factors may influence clinical outcomes.

7. Methodological limitations

This review has its own limits. In a narrative review, study selection reflects the search strategy and the authors' judgment and provides no formal risk-of-bias score or pooled estimate. Most included work consists of modest candidate-gene analyses, and small samples tend to overestimate effects.
The limitations encountered by clinical definitions are based on the use of different clinical guidelines: WHO 1997, 2009, and 2026. In addition, the available data analysis in the literature only partially covered populations across different countries and, as described in this report, results within a country may be heterogeneous depending on the collection site. Some studies focus on susceptibility to infection, while others focus on secondary infection and severity. Only a few studies analyze the responses of individuals who suffer only mild symptoms despite multiple infections.

8. Conclusions

Host genetic variation significantly influences the clinical course of dengue infection; however, the supporting evidence remains heterogeneous across studies and populations. The alleles HLA-A*24 and HLA-A*0203, as well as the MICB and PLCE1 loci, represent the most robust genetic associations identified to date, predominantly in Southeast Asian populations. Notably, DRB1*15 is the only allele to show a statistically significant association after multiple-testing correction in more than one Latin American cohort. The FCGR2A R/R131 polymorphism has been found to confer protection in some populations yet exhibits the opposite effect in Mexican cohorts. These findings underscore the importance of population-specific, serotype-aware analyses, as genetic associations vary according to population, serotype, and infection history. Studies involving Latin American and African cohorts are limited by small sample sizes, limiting the generalizability of their findings. Novel approaches provide a stronger rationale for analyzing host and population genetics in dengue infection. To analyze risk stratification in vaccine development and therapeutic targets, larger, multi-ethnic studies with harmonized case definitions and appropriate adjustment for genetic ancestry are required.

Author Contributions

Conceptualization, A.H.G. and J.B.D.S.; methodology, A.H.G. and J.B.D.S.; investigation, A.H.G. and J.B.D.S.; data curation, A.H.G. and J.B.D.S.; writing—original draft preparation, A.H.G. and J.B.D.S.; writing—review and editing, A.H.G. and J.B.D.S.; visualization, A.H.G. and J.B.D.S.; supervision, A.H.G. and J.B.D.S.; project administration, A.H.G. and J.B.D.S.; funding acquisition, A.H.G. and J.B.D.S. Both authors contributed equally to all aspects of the work and have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Fund for Science, Technology, and Innovation (FONACIT), an entity attached to the Ministry of Popular Power for Science and Technology of the Bolivarian Republic of Venezuela (MINCYT), and Corporación para el Desarrollo Científico (CODECYT). Project number 2024-207. J.B.D.S. is partially financed by the National Institute of Virology and Bacteriology (Program EXCELES, ID Project No. LX22NPO5103), funded by the European Union, Next Generation EU, and the Ministry of Education, Youth and Sports of the Czech Republic (MEYS).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No data was generated.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. World Health Organization. Dengue [Internet]. Geneva: World Health Organization; 2025 Aug 21 [cited 2026 Sep 20]. Available online: https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue.
  2. Lan, N.T.P.; Hirayama, K. Host genetic susceptibility to severe dengue infection. Trop. Med. Health 2011, 39, 73–81. [Google Scholar] [CrossRef]
  3. Bhatt, S.; Gething, P.W.; Brady, O.J.; Messina, J.P.; Farlow, A.W.; Moyes, C.L.; Drake, J.M.; Brownstein, J.S.; Hoen, A.G.; Sankoh, O.; et al. The global distribution and burden of dengue. Nature 2013, 496, 504–7. [Google Scholar] [CrossRef]
  4. https://www.cdc.gov/dengue/hcp/clinical-signs/index.html. Clinical Features of Dengue. February 2026. Assessed September 28, 2026.
  5. World Health Organization. Dengue: guidelines for diagnosis, treatment, prevention and control. New ed. Geneva: World Health Organization; 2009. Report No.: WHO/HTM/NTD/DEN/2009.1. Assessed August 30, 2026.
  6. García, A.H.; De Sanctis, J.B. Exploring the contrasts and similarities of dengue and SARS-CoV-2 infections during the COVID-19 era. Int. J. Mol. Sci. 2024, 25, 11624. [Google Scholar] [CrossRef]
  7. Vaughn, D.W.; Green, S.; Kalayanarooj, S.; Innis, B.L.; Nimmannitya, S.; et al. Dengue viremia titer, antibody response pattern, and virus serotype correlate with disease severity. J. Infect. Dis. 2000, 181, 2–9. [Google Scholar] [CrossRef]
  8. Rico-Hesse, R.; Harrison, L.M.; Salas, R.A.; Tovar, D.; Nisalak, A.; Ramos, C.; et al. Origins of dengue type 2 viruses associated with increased pathogenicity in the Americas. Virology 1997, 230, 244–51. [Google Scholar] [CrossRef]
  9. Salazar Flórez, J.E.; Segura Cardona, A.M.; Restrepo Jaramillo, B.N.; Arboleda Naranjo, M.; Giraldo Cardona, L.S.; Echeverri Rendón, A.P. Immune system gene polymorphisms associated with severe dengue in Latin America: a systematic review. Rev. Inst. Med. Trop. Sao Paulo 2023, 65, e58. [Google Scholar] [CrossRef]
  10. Mehak, M.A.; Khan, M.; Razu, M.H. Host factors and genetic polymorphisms influencing dengue infection. Virus Res. 2025, 360, 199623. [Google Scholar] [CrossRef]
  11. Fernández-Mestre, M.; Navarrete, C.V.; Brown, J.; Brown, C.; Correa, E.; Layrisse, Z. HLA alleles and dengue virus infection in Venezuelan patients: a preliminary study. Inmunología 2009, 28, 96–100. [Google Scholar] [CrossRef]
  12. de Alencar, L.X.E.; Braga-Neto, U.M.; do Nascimento, E.J.M.; Cordeiro, M.T.; Silva, A.M.; de Brito, C.A.A.; et al. HLA-B*44 is associated with dengue severity caused by DENV-3 in a Brazilian population. J. Trop. Med. 2013, 2013, 648475. [Google Scholar] [CrossRef]
  13. Cook, A.C.; Thibaut, D.; Pettersen, T. Major histocompatibility complex class I and dengue hemorrhagic fever: a meta-analysis of human leukocyte antigens A*24 and B*44. Cureus 2022, 14, e31485. [Google Scholar] [CrossRef]
  14. Silva, L.K.; Blanton, R.E.; Parrado, A.R.; Melo, P.S.; Morato, V.G.; Reis, E.A.; et al. Dengue hemorrhagic fever is associated with polymorphisms in JAK1. Eur. J. Hum. Genet. 2010, 18, 1221–7. [Google Scholar] [CrossRef]
  15. Khor, C.C.; Chau, T.N.B.; Pang, J.; Davila, S.; Long, H.T.; Ong, R.T.H.; et al. Genome-wide association study identifies susceptibility loci for dengue shock syndrome at MICB and PLCE1. Nat. Genet. 2011, 43, 1139–41. [Google Scholar] [CrossRef]
  16. Ghosh, A.G.; Kim, H.L.; Khor, S.S. HLA alleles and dengue susceptibility across populations in the era of climate change: a comprehensive review. Front Immunol. 2025, 16, 1473475. [Google Scholar] [CrossRef]
  17. Asaga, P.M.; Kadukkatti, V.; Airiohuodion, P.; Danaan, D.A.; Ibeh, D.C.; Kroeger, A. Viral and host determinants of arboviral disease severity in African populations: a systematic review with meta-analysis. PLoS Negl. Trop. Dis. 2026, 20, e0014663. [Google Scholar] [CrossRef]
  18. Haider, N.; Hasan, M.N.; Onyango, J.; Billah, M.; Khan, S.; Papakonstantinou, D.; Paudyal, P.; Asaduzzaman, M. Global dengue epidemic worsens with record 14 million cases and 9000 deaths reported in 2024. Int. J. Infect. Dis. 2025, 158, 107940. [Google Scholar] [CrossRef]
  19. https://www.paho.org/en/documents/epidemiological-update-dengue-americas-region-18-february-2026. Assessed September 20, 2026.
  20. Del Pilar Fortes, M.; Gill, G.; Paredes, M.E.; Gamez, L.E.; Palacios, M.; Blanca, I.; Tassinari, P. Allele and haplotype frequencies at human leukocyte antigen class I and II genes in Venezuela's population. Ann. Biol. Clin. 2012, 70, 175–81. [Google Scholar] [CrossRef]
  21. Loke, H.; Bethell, D.B.; Phuong, C.X.T.; Dung, M.; Schneider, J.; White, N.J.; et al. Strong HLA class I-restricted T cell responses in dengue hemorrhagic fever: a double-edged sword? J. Infect. Dis. 2001, 184, 1369–73. [Google Scholar] [CrossRef]
  22. Lan, N.T.; Kikuchi, M.; Vu, T.Q.; Do, Q.H.; Tran, T.T.; Vo, D.T.; et al. Protective and enhancing HLA alleles, HLA-DRB1*0901 and HLA-A*24, for severe forms of dengue virus infection, dengue hemorrhagic fever and dengue shock syndrome. PLoS Negl. Trop. Dis. 2008, 2, e304. [Google Scholar] [CrossRef]
  23. Chen, Y.; Liao, Y.; Yuan, K.; Wu, A.; Liu, L. HLA-A, -B, -DRB1 alleles as genetic predictive factors for dengue disease: a systematic review and meta-analysis. Viral Immunol. 2019, 32, 121–30. [Google Scholar] [CrossRef]
  24. Appanna, R.; Ponnampalavanar, S.; Lum Chai See, L.; Sekaran, S.D. Susceptible and protective HLA class 1 alleles against dengue fever and dengue hemorrhagic fever patients in a Malaysian population. PLoS ONE 2010, 5, e13029. [Google Scholar] [CrossRef]
  25. Stephens, H.A.F.; Klaythong, R.; Sirikong, M.; Vaughn, D.W.; Green, S.; Kalayanarooj, S.; et al. HLA-A and -B allele associations with secondary dengue virus infections correlate with disease severity and the infecting viral serotype in ethnic Thais. Tissue Antigens 2002, 60, 309–18. [Google Scholar] [CrossRef]
  26. Vejbaesya, S.; Luangtrakool, P.; Luangtrakool, K.; Kalayanarooj, S.; Vaughn, D.W.; Endy, T.P.; et al. TNF and LTA gene, allele, and extended HLA haplotype associations with severe dengue virus infection in ethnic Thais. J. Infect. Dis. 2009, 199, 1442–8. [Google Scholar] [CrossRef]
  27. Sierra, B.; Alegre, R.; Pérez, A.B.; García, G.; Sturn-Ramírez, K.; Obasanjo, O.; et al. HLA-A, -B, -C, and -DRB1 allele frequencies in Cuban individuals with antecedents of dengue 2 disease: advantages of the Cuban population for HLA studies of dengue virus infection. Hum. Immunol. 2007, 68, 531–40. [Google Scholar] [CrossRef]
  28. LaFleur, C.; Granados, J.; Vargas-Alarcón, G.; Ruiz-Morales, J.; Villarreal-Garza, C.; Higuera, L.; et al. HLA-DR antigen frequencies in Mexican patients with dengue virus infection: HLA-DR4 as a possible genetic resistance factor for dengue hemorrhagic fever. Hum. Immunol. 2002, 63, 1039–44. [Google Scholar] [CrossRef]
  29. Polizel, J.R.; Bueno, D.; Visentainer, J.E.L.; Sell, A.M.; Borelli, S.D.; Tsuneto, L.T.; et al. Association of human leukocyte antigen DQ1 and dengue fever in a white Southern Brazilian population. Mem. Inst. Oswaldo Cruz 2004, 99, 559–62. [Google Scholar] [CrossRef]
  30. Cardozo, D.M.; Moliterno, R.A.; Sell, A.M.; Guelsin, G.A.S.; Beltrame, L.M.; Clementino, S.L.; et al. Evidence of HLA-DQB1 contribution to susceptibility of dengue serotype 3 in dengue patients in Southern Brazil. J. Trop. Med. 2014, 2014, 968262. [Google Scholar] [CrossRef]
  31. Traoré, L.; Kouta, O.F.; Tapsoba, A.S.A.; Ouattara, A.K.; Kanfon, R.; Yougbaré, M.R.; et al. Involvement of HLA-DRB1*11 and HLA-DRB1*12 alleles in the occurrence of dengue fever in Burkina Faso. J. Exp. Mol. Biol. 2025, 26, 1–12. [Google Scholar] [CrossRef]
  32. Sorgho, P.A.; Kafando, A.O.; Ouedraogo, R.A.; Kabre, K.M.; Nacoulma, S.F.; Adico, M.D.W.; et al. HLA-DRB1*03 and HLA-DRB1*04 alleles in patients infected with dengue virus in Burkina Faso. Infect. Genet Evol. 2026, 143, 105983. [Google Scholar] [CrossRef]
  33. Cahill, M.E.; Conley, S.; DeWan, A.T.; Montgomery, R.R. Identification of genetic variants associated with dengue or West Nile virus disease: a systematic review and meta-analysis. BMC Infect. Dis. 2018, 18, 282. [Google Scholar] [CrossRef]
  34. Fernández-Mestre, M.T.; Gendzekhadze, K.; Rivas-Vetencourt, P.; Layrisse, Z. TNF-alpha-308A allele, a possible severity risk factor of hemorrhagic manifestation in dengue fever patients. Tissue Antigens 2004, 64, 469–72. [Google Scholar] [CrossRef]
  35. Naing, C.; Htet, N.H.; Siew Tung, W.; Basavaraj, A.K.; Mak, J.W. Association of tumour necrosis factor-α (TNF-α) gene polymorphisms (-308 G>A and -238 G>A) and the risk of severe dengue: a meta-analysis and trial sequential analysis. PLoS One 2018, 13, e0205413. [Google Scholar] [CrossRef]
  36. Useche, Y.M.; Ribeiro-Alves, M.; Restrepo, B.N.; Salgado, D.M.; Narváez, C.F.; Campo, O.; et al. Single-nucleotide polymorphisms in NOD1, RIPK2, MICB, PLCE1, TNF, and IKBKE genes associated with symptomatic dengue in children from Colombia. Viral Immunol. 2018, 31, 1–11. [Google Scholar] [CrossRef]
  37. Avendaño-Tamayo, E.; Campo, O.; Chacón-Duque, J.C.; Ramírez, R.; Rojas, W.; Agudelo-Flórez, P.; et al. Variantes en los genes TNFA, IL6 e IFNG asociadas con la gravedad del dengue en una muestra de población colombiana. Biomédica 2017, 37, 485–97. [Google Scholar] [CrossRef]
  38. Santos, A.C.; de Moura, E.L.; Ferreira, J.M.; Santos, B.R.; Alves, V.M.; de Farias, K.F.; de Souza Figueiredo, E.V. Meta-Analysis of the Relationship between TNF-α (-308G/A) and IL-10 (-819C/T) Gene Polymorphisms and Susceptibility to Dengue. Immunol. Invest. 2017, 46, 201–220. [Google Scholar] [CrossRef]
  39. Chacón-Duque, J.C.; Adhikari, K.; Avendaño, E.; Campo, O.; Ramirez, R.; Rojas, W.; Ruiz-Linares, A.; Restrepo, B.N.; Bedoya, G. African genetic ancestry is associated with a protective effect on Dengue severity in Colombian populations. Infect. Genet Evol. 2014, 27, 89–95. [Google Scholar] [CrossRef]
  40. Alagarasu, K.; Mulay, A.P.; Singh, R.; Gavade, V.B.; Shah, P.S.; Cecilia, D. Association of HLA-DRB1 and TNF genotypes with dengue hemorrhagic fever. Hum. Immunol. 2013, 74, 610–7. [Google Scholar] [CrossRef]
  41. Loke, H.; Bethell, D.; Phuong, C.X.T.; Day, N.; White, N.; Farrar, J.; et al. Susceptibility to dengue hemorrhagic fever in Vietnam: evidence of an association with variation in the vitamin D receptor and Fc gamma receptor IIa genes. Am. J. Trop. Med. Hyg. 2002, 67, 102–6. [Google Scholar] [CrossRef]
  42. García, G.; Sierra, B.; Pérez, A.B.; Aguirre, E.; Rosado, I.; González, N.; et al. Asymptomatic dengue infection in a Cuban population confirms the protective role of the RR variant of the FcγRIIa polymorphism. Am. J. Trop. Med. Hyg. 2010, 82, 1153–6. [Google Scholar] [CrossRef]
  43. García, G.; González, D.; Sánchez, L.; Pérez, A.B.; Sierra, B.; Guzmán, M.G. Polimorfismo del receptor FcγRIIa y su posible relación con las manifestaciones clínicas del dengue. Enferm. Infecc. Microbiol. Clin. 2012, 30, 621–3. [Google Scholar] [CrossRef]
  44. Noecker, C.A.; Amaya-Larios, I.Y.; Galeana-Hernández, M.; Ramos-Castaneda, J.; Martínez-Vega, R.A. Contrasting associations of polymorphisms in FcγRIIa and DC-SIGN with the clinical presentation of dengue infection in a Mexican population. Acta Trop. 2014, 138, 15–22. [Google Scholar] [CrossRef]
  45. Sakuntabhai, A.; Turbpaiboon, C.; Casadémont, I.; Chuansumrit, A.; Lowhnoo, T.; Kajaste-Rudnitski, A.; et al. A variant in the CD209 promoter is associated with severity of dengue disease. Nat. Genet. 2005, 37, 507–13. [Google Scholar] [CrossRef]
  46. Oliveira, L.F.; Lima, C.P.; Azevedo Rdo, S.; Mendonça, D.S.; Rodrigues, S.G.; Carvalho, V.L.; Pinto, E.V.; Maia, A.L.; Maia, M.H.; Vasconcelos, J.M.; et al. Polymorphism of DC-SIGN (CD209) promoter in association with clinical symptoms of dengue fever. Viral Immunol. 2014, 27, 245–9. [Google Scholar] [CrossRef]
  47. Wang, L.; Chen, R.F.; Liu, J.W.; Lee, I.K.; Lee, C.P.; Kuo, H.C.; et al. DC-SIGN (CD209) promoter -336 A/G polymorphism is associated with dengue hemorrhagic fever and correlated to DC-SIGN expression and immune augmentation. PLoS Negl. Trop. Dis. 2011, 5, e934. [Google Scholar] [CrossRef]
  48. Alagarasu, K.; Damle, I.M.; Bachal, R.V.; Mulay, A.P.; Shah, P.S.; Dayaraj, C. Association of promoter region polymorphisms of CD209 gene with clinical outcomes of dengue virus infection in Western India. Infect. Genet Evol. 2013, 17, 239–42. [Google Scholar] [CrossRef]
  49. Dang, T.N.; Naka, I.; Sa-Ngasang, A.; Anantapreecha, S.; Wichukchinda, N.; Sawanpanyalert, P.; et al. Association of BAK1 single nucleotide polymorphism with a risk for dengue hemorrhagic fever. BMC Med. Genet. 2016, 17, 43. [Google Scholar] [CrossRef]
  50. Yougbare, F.; Tapsoba, A.S.A.; Sorgho, P.A.; Bayala, B.; Traore, L.; Bado, P.; et al. DC-SIGN (CD209) promoter -336 A/G polymorphism is not associated with dengue fever at Burkina Faso, West Africa. J. Biosci. Med. 2023, 11, 175–83. [Google Scholar]
  51. Xavier-Carvalho, C.; Gibson, G.; Brasil, P.; Ferreira, R.X.; de Souza Santos, R.; Gonçalves Cruz, O.; et al. Single nucleotide polymorphisms in candidate genes and dengue severity in children: a case-control, functional and meta-analysis study. Infect. Genet Evol. 2013, 20, 197–205. [Google Scholar] [CrossRef]
  52. Ren, J.; Wang, Z.; Chen, E. Different associations between DC-SIGN promoter -336G/A (rs4804803) polymorphism with severe dengue in Asians and South-Central Americans: a meta-analysis. Int. J. Environ. Res. Public Health 2019, 16, 1475. [Google Scholar] [CrossRef]
  53. Soundravally, R.; Hoti, S.L. Immunopathogenesis of dengue hemorrhagic fever and shock syndrome: role of TAP and HPA gene polymorphism. Hum. Immunol. 2007, 68, 973–9. [Google Scholar] [CrossRef]
  54. Ornelas, A.M.M.; Xavier-de-Carvalho, C.; Alvarado-Arnez, L.E.; Ribeiro-Alves, M.; Rossi, Á.D.; Tanuri, A.; de Aguiar, R.S.; Moraes, M.O.; Cardoso, C.C. Association between MBL2 haplotypes and dengue severity in children from Rio de Janeiro, Brazil. Mem. Inst. Oswaldo Cruz 2019, 114, e190004. [Google Scholar] [CrossRef]
  55. Sena, M.A.; da Silva Castanha, P.M.; Giles Guimarães, A.B.; Oliveira, P.A.D.S.; da Silva, M.A.L.; Cordeiro, M.T.; Moura, P.; Braga, C.; Vasconcelos, L.R.S. Mannose-binding lectin levels and MBL2 gene polymorphisms are associated with dengue infection in Brazilian children at the early ages. Int. J. Infect. Dis. 2022, 117, 212–219. [Google Scholar] [CrossRef]
  56. Giang, N.T.; van Tong, H.; Quyet, D.; Hoan, N.X.; Nghia, T.H.; Nam, N.M.; Hung, H.V.; Anh, D.T.; Van Mao, C.; Son, H.A.; et al. Complement protein levels and MBL2 polymorphisms are associated with dengue and disease severity. Sci. Rep. 2020, 10, 14923. [Google Scholar] [CrossRef]
  57. Acioli-Santos, B.; Segat, L.; Dhalia, R.; Brito, C.A.A.; Braga-Neto, U.M.; Marques, E.T.A.; et al. MBL2 gene polymorphisms protect against development of thrombocytopenia associated with severe dengue phenotype. Hum. Immunol. 2008, 69, 122–8. [Google Scholar] [CrossRef]
  58. Tapsoba, A.S.A.; Djigma, F.W.; Bayala, B.; Sorgho, P.A.; Traore, L.; Zohoncon, T.M.; et al. KIR2DL2, KIR2DL5A and KIR2DL5B genes induce susceptibility to dengue virus infection, while KIR3DL3 and KIR2DS5 confer protection. Mediterr. J. Hematol. Infect. Dis. 2022, 14, e2022075. [Google Scholar] [CrossRef]
  59. Beltrame, L.M.; Sell, A.M.; Moliterno, R.A.; Clementino, S.L.; Cardozo, D.M.; Dalalio, M.M.; et al. Influence of KIR genes and their HLA ligands in susceptibility to dengue in a population from southern Brazil. Tissue Antigens 2013, 82, 397–404. [Google Scholar] [CrossRef]
  60. Alagarasu, K.; Bachal, R.V.; Shah, P.S.; Cecilia, D. Profile of killer cell immunoglobulin-like receptor and its human leucocyte antigen ligands in dengue-infected patients from Western India. Int. J. Immunogenet. 2015, 42, 432–8. [Google Scholar] [CrossRef]
  61. Candrasari, D.S.; Purwosatrio, P.G.; Purnomosari, D.; Laksanawati, I.S.; Nirwati, H. Host genetic factors modulating dengue virus: a systematic review of TLR polymorphisms. BMC Infect. Dis. 2026, 26, 399. [Google Scholar] [CrossRef]
  62. Diep, N.T.; Giang, N.T.; Diu, N.T.T.; Nam, N.M.; Khanh, L.V.; Quang, H.V.; Hang, N.T.; Mao, C.V.; Son, H.V.; Hieu, N.L.; Linh, P.T.; Sklan, E.H.; Toan, N.L.; Tong, H.V. Complement receptor type 1 and 2 (CR1 and CR2) gene polymorphisms and plasma protein levels are associated with the Dengue disease severity. Sci. Rep. 2023, 13, 17377. [Google Scholar] [CrossRef]
  63. Whitehorn, J.; Chau, T.N.B.; Nguyet, N.M.; Kien, D.T.H.; Quyen, N.T.H.; Trung, D.T.; et al. Genetic variants of MICB and PLCE1 and associations with non-severe dengue. PLoS ONE 2013, 8, e59067. [Google Scholar] [CrossRef]
  64. García, G.; del Puerto, F.; Pérez, A.B.; Sierra, B.; Aguirre, E.; Kikuchi, M.; et al. Association of MICA and MICB alleles with symptomatic dengue infection. Hum. Immunol. 2011, 72, 904–7. [Google Scholar] [CrossRef]
  65. Oliveira, M.; Saraiva, D.P.; Cavadas, B.; Fernandes, V.; Pedro, N.; Casademont, I.; et al. Population genetics-informed meta-analysis in seven genes associated with risk to dengue fever disease. Infect. Genet Evol. 2018, 63, 213–23. [Google Scholar] [CrossRef]
  66. Sierra, B.; Triska, P.; Soares, P.; Garcia, G.; Perez, A.B.; Aguirre, E.; et al. OSBPL10, RXRA and lipid metabolism confer African-ancestry protection against dengue haemorrhagic fever in admixed Cubans. PLoS Pathog. 2017, 13, e1006220. [Google Scholar] [CrossRef]
  67. Sayem, M.; Rimon, R.A.; Alam, S.; Saba, A.A.; Sanyal, M.; Sayem, M.; Tabassum, C.T.; Amin, M.R.; Chakraborty, S.; Kabir, A.; Nabi, A.H.M.N. Genetic variability in thrombopoietin receptor and GATA1 influences response to eltrombopag in dengue-induced thrombocytopenia. Sci. Rep. 2026, 16, 7918. [Google Scholar] [CrossRef]
  68. Gokul, A.; Arumugam, T.; Ramsuran, V. Genetic Ethnic Differences in Human 2′-5′-Oligoadenylate Synthetase and Disease Associations: A Systematic Review. Genes 2023, 14, 527. [Google Scholar] [CrossRef]
  69. Mesev, E.V.; LeDesma, R.A.; Ploss, A. Decoding type I and III interferon signaling during viral infection. Nat. Microbiol. 2019, 4, 914–924. [Google Scholar] [CrossRef]
  70. Granela, H.; Perez, A.B.; Morier, L.; Alvarez, M.; Guzmán, M.G.; Sierra, B. Possible effects of ancestry-related oxysterol-binding protein-like 10 genetic polymorphisms on dengue virus replication and anti-dengue immune response. Heliyon 2024, 10, e37535. [Google Scholar] [CrossRef]
  71. Gainor, E.M.; Harris, E.; LaBeaud, A.D. Uncovering the Burden of Dengue in Africa: Considerations on Magnitude, Misdiagnosis, and Ancestry. Viruses 2022, 14, 233. [Google Scholar] [CrossRef]
  72. Bello, M.B.; Aljedani, S.S.; Lawal, N.; Alasiri, A.; Imam, M.U. Evolutionary history and transmission dynamics of dengue virus type 2 in Africa. Front Microbiol. 2026, 17, 1782819. [Google Scholar] [CrossRef]
  73. Kalayanarooj, S.; Gibbons, R.V.; Vaughn, D.; Green, S.; Nisalak, A.; Jarman, R.G.; Mammen, M.P., Jr.; Perng, G.C. Blood group AB is associated with increased risk for severe dengue disease in secondary infections. J. Infect. Dis. 2007, 195, 1014–7. [Google Scholar] [CrossRef]
  74. Ravichandran, S.; Ramya, S.R.; Kanungo, R. Association of ABO blood groups with dengue fever and its complications in a tertiary care hospital. J. Lab Physicians 2019, 11, 265–269. [Google Scholar] [CrossRef]
  75. Tassembedo, F.; Tapsoba, A.S.A.; Bello, S.O.T.; Kouta, O.F.; Savadogo, M.; Ouedraogo, R.A.; Ilboudo, D.P.; Traore, L.; Yougbare, F.; Nagalo, B.M.; et al. TNF-α 308 (rs1800629) and INF-γ +874 polymorphisms in dengue progression: genotype-specific trends amidst allelic non-association in West Africa. Cell Mol. Biol. (Noisy-le-grand) 2025, 71, 1–8. [Google Scholar] [CrossRef]
  76. Boillat-Blanco, N.; Klaassen, B.; Mbarack, Z.; Samaka, J.; Mlaganile, T.; Masimba, J.; et al. Dengue fever in Dar es Salaam, Tanzania: clinical features and outcome in populations of black and non-black racial category. BMC Infect. Dis. 2018, 18, 644. [Google Scholar] [CrossRef]
  77. Ouedraogo, A.R.; Traoré, L.; Ouattara, A.K.; Ouedraogo, A.R.; Zongo, S.V.; Savadogo, M.; Lallogo, T.D.; Sombie, H.K.; Sorgho, P.A.; Ouedraogo, T.C.; et al. Association of HLA-DRB1*11 and HLA-DRB1*12 gene polymorphism with COVID-19 in Burkina Faso. BMC Med. Genom. 2023, 16, 246. [Google Scholar] [CrossRef]
  78. Latif, M.A.; Noman, M.A.; Ahmmed, R.; Hossain, M.S.; Ahmed, M.F.; Pappu, M.A.A.; Islam, M.S.; Noor, T.; Kabir, M.H.; Mollah, M.N.H. In-silico identification of host-key-genes associated with dengue-virus-infections highlighting their pathogenetic mechanisms and therapeutic agents. PLoS ONE 2025, 20, e0333509. [Google Scholar] [CrossRef]
  79. Josyula, J.V.N.; Jangili, S.; Yaladanda, N.; Pillai, A.K.B.; Mutheneni, S.R. Exploring potential gene signatures in dengue through machine learning and deep learning approaches. Virus Genes. 2026, 62, 51–66. [Google Scholar] [CrossRef]
  80. Datta, D.; Ghosh, S. Analyzing the Molecular Signature Genes and Pathways of Dengue Fever, Dengue Hemorrhagic Fever and Dengue Shock Syndrome Caused by Dengue Virus in India. Mol. Biotechnol. 2026, 68, 777–794. [Google Scholar] [CrossRef]
  81. Kenney, A.D.; Dowdle, J.A.; Bozzacco, L.; McMichael, T.M.; St Gelais, C.; Panfil, A.R.; Sun, Y.; Schlesinger, L.S.; Anderson, M.Z.; Green, P.L.; López, C.B.; Rosenberg, B.R.; Wu, L.; Yount, J.S. Human Genetic Determinants of Viral Diseases. Annu Rev. Genet. 2017, 51, 241–263. [Google Scholar] [CrossRef]
  82. Khare, K.; Yadav, S.; Tarai, B.; Budhiraja, S.; Pandey, R. TCR repertoire dynamics and their responses underscores dengue severity. iScience 2024, 27, 110983. [Google Scholar] [CrossRef]
  83. Yoo, J.S.; Shporn, O.Z.; Sklan, E.H. Dysregulated immune cell responses in severe dengue pathogenesis. Front Immunol. 2025, 16, 1600999. [Google Scholar] [CrossRef]
  84. Nguyen, A.T.; Szeto, C.; Gras, S. The pockets guide to HLA class I molecules. Biochem Soc. Trans. 2021, 49, 2319–2331. [Google Scholar] [CrossRef]
  85. Magyari, B.; Fülöp, A.T.; Kókai, D.; Tóth, F.; Balogh, G.M.; Andreu-Sánchez, S.; Innocenti, G.; Weersma, R.K.; Fu, J.; Pál, C.; Zhernakova, A.; Vogl, T.; Manczinger, M. HLA-II peptide-binding diversity shapes humoral immune responses and susceptibility to infections. Nat. Commun. 2026, 17, 9422. [Google Scholar] [CrossRef]
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