ApoE Polymorphism Analysis in Health and Disease of South Asian Populations

ApoE Polymorphism Analysis in Health and Disease of South Asian Populations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article ApoE Polymorphism Analysis in Health and Disease of South Asian Populations Prayash Paudel, Asutosh Sah, Poonam Paudel This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5554316/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This systematic review and meta-analysis assesses the distribution and health implications of apolipoprotein E (ApoE) ε2, ε3, and ε4 alleles, which play crucial roles in lipoprotein metabolism, in South Asian populations, with a focus on neurodegenerative diseases, movement disorders, mental health disorders, cardiovascular disorders, metabolic disorders and trauma-related disorders. A total of 53 studies identified through comprehensive searches in PubMed, Embase, and Google Scholar up to July 31, 2024, were included on the basis of predefined eligibility criteria after Risk Of Bias Assessment via the New York Ottawa Scale. ε3/ε3 was found to be the most prevalent genotype, followed by ε3/ε4 and ε2/ε3. ε4-containing genotypes were found to be strongly associated with susceptibility to Alzheimer's disease, coronary artery disease, vascular dementia, and obesity, whereas the ε2/ε3 and ε2 alleles showed protective effects in some conditions. These studies had several limitations, including data gaps for specific health conditions, underrepresentation of some South Asian countries, and heterogeneity in outcomes. Despite gaps in the data from a number of countries and for specific health conditions under study, this review reflects South Asian specificity of ApoE polymorphism‒disease associations, highlighting the need for targeted genetic research and tailored public health strategies to advance personalized medicine and healthcare policies in this region. There was no specific funding for this study. The study was registered in PROSPERO (registration number CRD42024575197). Biological sciences/Biochemistry Biological sciences/Genetics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Apolipoprotein E is a glycoprotein that plays a critical role in the regulation of cholesterol homeostasis and lipid metabolic processes. Mainly, it is produced by hepatocytes and astrocytes and is expressed in plasma and cerebrospinal fluid[1]. The three most common polymorphisms, which are products of three alleles (ε2, ε3 and ε4) at a single gene locus, are E2, E3 and E4[2]. As reviewed by [3], the ε3 allele is the most common allele, occurring in ~77% of the general population, whereas the ε2 allele accounts for ~8%, and the ε4 allele accounts for ~15%. ApoE3 is considered the parent form, being Cys112 and Arg158, whereas apoE4 is Arg112 and Arg158, and apoE2 is Cys112 and Cys158 [2]. Overall, six phenotypes are possible, with their ranking from most to least common being E3/3, E4/3, E3/2, E4/4, E4/2, and E2/2 [4]. ApoE is involved mainly in lipid metabolism, although to date, it has been revealed to be important in other processes, such as neuroprotection, antimicrobial defense, oxidative stress, and inflammation [5]. ApoE binds via its surface-exposed aromatic ring to LDL receptor family members and hence participates in cholesterol transport [6]. A linear relationship was observed between the apoE genotype (ε2/ε2 > ε2/ε3 > ε2/ε4 > ε3/ε3 > ε3/ε4 > ε4/ε4) and both LDL-cholesterol levels and coronary artery diseases [7]. In the vascular wall, apoE secreted by macrophages participates in cellular cholesterol efflux from the atheroma [8]. ApoE secreted by macrophages mediates cholesterol efflux, thus preventing cholesterol overload and subsequent conversion into foam cells [9]. Cullen et al. reported that apoE isoforms differentially regulate cholesterol metabolism in human monocyte-derived macrophages as follows: E2/2 > E3/3 ≅ E4/4 [10]. APOE ε2-related genotypes might be protective factors for MI, whereas ε4-related genotypes (ε4/ε3 vs. ε3/ε3 and ε4/ε4 vs. ε3/ε3) could be risk factors for MI [11]. In the brain, astrocytes represent the main supplier of apoE, which is the most abundant apolipoprotein in the cerebrospinal fluid [12]. Owing to its role in the transport of lipids, apoE performs important functions in brain homeostasis, regulating lipid and glucose metabolism and effectively preserving and remodelling neuronal signalling [13–15]. In the brain, apoE is provided by astrocytes, assembled in lipoproteins and then transported to neurons where it is taken up via LDL receptor superfamily members localized on the surface of the neurons [16]. Abyadeh et al. [17] performed a meta-analysis showing the association between the APOE ε4 allele and susceptibility to AD among an Iranian population, whereas APOE ε3 had a protective role against this devastating disorder. No significant association was observed between APOE ε2 and AD, although evidence indicating the protective role of the APOE ε2 allele is available. A meta-analysis by Yin et al. (2012) [18] with a total of 29 studies including 1763 VaD cases suggested an association between ApoE 4 mutation and increased risk of VaD. In the meta-analysis by Lamb et al. (1998), the ε2 allele frequency in DLB was found to be rather similar to that of the control group, at 9.2% and 8.9%, respectively, and may therefore have some protective effect. The ε3 allele is less common in DLB patients (55.1%) than in controls (76.2%), and only 8% of DLB patients were ε4/ε4 homozygotes, reflecting the lesser impact of ε4 homozygosity in DLB. A meta-analysis by Feng et al. (2015) (Feng et al., 2015) suggested that the e2/e3 genotype likely provided a protective effect against depression in the overall population. The ApoE e2 allele acts as a protective factor against depression in the Caucasian population. The e4 allele and e3/e4 genotype were associated with an increased risk of depression in patients aged 50 years or over. The meta-analysis of Su et al. (2017) [20] showed that the APOE ε4 allele significantly increased the risk for developing frontotemporal lobar degeneration (FTLD) through all investigated genetic models: ε4 vs. ε3, ε4 vs. ε2, ε4 vs. ε2+ε3+ε4, and ε4 carrier models. This finding was also confirmed in subgroup analyses in Caucasians, Italians, and patients with behavioral variant frontotemporal dementia (bvFTD). Conversely, the ε2 allele of APOE was not significantly associated with FTLD in most genetic models. These findings suggest that ε4, but not ε2, may be a genetic risk factor for FTLD. The results of an analysis by Banning et al. (2019) [21] revealed that APOE ε4 is related to a slightly increased incidence of MCI. Compared with noncarriers, ε4 carriers presented a more pronounced decline in cognitive ability, although the effect itself was highly variable across studies and due to differences in population characteristics. In contrast, the APOE ε2 allele was not significantly associated with the incidence of MCI. These findings confirmed ε4 as a genetic risk factor for MCI. Significantly, the meta-analysis of Qiao et al. (2022) indicated that the APOE ε4 allele is associated with an increased risk for IS, where ε4 carriers have an increased risk compared with nonε4 carriers, with a pooled OR of 1.377. The results provided evidence of a dose response, where ε4/ε4 homozygotes presented extremely high risk, with an OR of 1.833 compared with the ε3/ε3 or ε3/ε4 genotypes. We found that the ε4 mutation was specifically linked to increased susceptibility to the small artery disease (SAD) subtype of ischaemic stroke (IS), although this mutation was not detected in patients with large artery atherosclerosis or cardio-aortic embolism. These findings suggest that APOE ε4 plays a dose-dependent role in the risk of IS SAD subtype cases. Wu et al. (2022) [22] noted in their meta-analysis that the APOE ε4 allele is especially associated with type 2 diabetes mellitus (T2DM) because of its relationship with lipid abnormalities. More precisely, in patients with T2DM, this ε4 allele is associated with higher LDL-C and lower high-density lipoprotein cholesterol (HDL-C), thus presenting a more atherogenic lipid profile. Thus, such genetic polymorphisms may increase the risk for dyslipidemia, which in turn can lead to perturbation of metabolic equilibrium and exacerbate T2DM manifestations. ApoE polymorphisms, encompassing the ε2, ε3, and ε4 alleles, are integral to lipid metabolism and are considered risk factors for various neurodegenerative and cardiovascular diseases. Surprisingly, however, few or no comprehensive data have been reported on the distribution of ApoE alleles and their health consequences in the context of South Asia, with rapidly increasing burdens of diseases such as Alzheimer's disease, coronary artery disease, and diabetes. Since most studies on ApoE have been conducted in Western populations, whose genetic constitution and lifestyle differ substantially from those of South Asia, the region-specific effects of ApoE polymorphisms need to be understood. This meta-analysis thus becomes imperative to meet the pressing need for focused, region-specific inputs that could lead to improvements in public health strategies, personalized medicine, and preventive care in South Asian populations. This systematic review focuses on the determination of the distribution and health effects of the ApoE polymorphisms represented by the ε2, ε3, and ε4 alleles in South Asian populations. In accordance with the PICOS framework, this review focuses on studies conducted on human participants of South Asian origin, with a specific focus on ApoE genetic variants. The evaluated intervention would be the presence of specific ApoE polymorphisms, expressed as alleles ε2, ε3, and ε4. Comparisons are then made among these different genotypes regarding their associations with various health outcomes, such as cardiovascular diseases, Alzheimer's disease, and other metabolic and neurodegenerative conditions. The outcomes of interest were the frequency of the alleles in South Asian populations and the associated disease risk linked to each genotype. This review covers observational studies, case‒control studies, and cohort studies to systematically evaluate the evidence concerning ApoE polymorphisms and their health effects in this regional context. Despite the large volume of literature concerning the role of ApoE polymorphisms in different pathologies, there are certain gaps in the literature review. To date, no meta-analyses have been conducted on the associations of ApoE polymorphisms with PD, metabolic syndrome, or obesity. There is also a shortage of studies regarding the interplay between obesity and traumatic brain injury in the context of ApoE polymorphisms. These gaps indicate that further focused research is needed for a complete understanding of the implications of ApoE polymorphisms in these aspects. Inclusion Criteria Studies conducted on human participants from South Asian countries (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka). Studies that reported on ApoE polymorphisms (ε2, ε3, ε4) and their distribution or association with health outcomes . Observational studies (cross-sectional, case–control, or cohort designs). Studies with sufficient genotype/allele data to allow extraction or computation of effect sizes. Full-text articles published in English . Exclusion Criteria Studies not involving South Asian populations or not reporting data separately for them. Reviews, editorials, case reports, or conference abstracts . Studies without ApoE genotype data or lacking relevant outcome associations. Articles with insufficient data or unavailable full texts despite reasonable effort. Duplicate reports of the same dataset (only the most complete or recent included). Methods Design This systematic review and meta-analysis followed the principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. The PRISMA diagram detailing the selection process is shown in Figure 1. The study protocol was registered at PROSPERO with reference CRD42024575197 before beginning the study. The full checklist and protocol for this study are included in S4_Appendix and S5_Appendix. Search strategy The PubMed, Embase and Google Scholar databases were searched up to 31 July 2024. Studies were also obtained from supplementary sources, manual searches, and other repositories. Cross-references from the published articles were manually searched to retrieve additional literature. To create an extensive search strategy that encompassed all fields in the records as well as Medical Subject Headings (MeSH words) for broadening the search in an advanced PubMed search, the predefined phrases were identified. For PubMed, meshes of related terms and keywords combined with Boolean operators (AND, OR) were used for the systematic identification of records. The names of South Asian countries—Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka—were combined with search terms. The preliminary search strategy is described in S2_Appendix. For Google Scholar, the keywords “ApoE” and “Polymorphism” were used along with each southern Asian country. Selection of studies The literature search was performed by PP and AS. The included studies were exported to Google Sheets in compatible format. Duplicate articles were screened manually. Duplicates were then recorded and removed. After removing duplicates, two independent authors, PP and AS, screened the title and abstract of every article that remained. Full-text articles were obtained for the relevant studies satisfying the inclusion criteria. The data were extracted by the two authors, PP and AS, independently. Disagreements were resolved by consulting with a third author (PP) whenever necessary. Data extraction The following data were extracted from the studies: name of the author, year of publication, country of study, sample size, percentage of the male population, mean age of the population and associated comorbidities. Quality assessment of the studies Two independent reviewers (PP and AS) conducted the quality assessment for the included studies via the Newcastle‒Ottawa Scale (NOS), adapted for cross-sectional studies. Disagreements were resolved by consulting with a third author (PP) whenever necessary. The assessment framework had a maximum score of 10, with scores of seven or higher indicating a low risk of bias. The additional methodological details can be found in supplementary material S3_Appendix. Statistical analysis Pooled genotype proportions for six genotypes and allele frequencies for three alleles were calculated along with 95% confidence intervals (95% CI) for the general population via a random effect model with a raw proportion function. For each disease, logarithms of odds ratios (log ORs) are calculated for individual ApoE genotypes compared with the reference genotype (E3/E3). We used the e3e3 genotype as a reference since it is the most common genotype. The logarithms of the odds ratios (log ORs) and 95% confidence intervals (95% CIs) for each genotype for a representative outcome from each distinct disease are presented as forest plots. Heterogeneity was evaluated via the χ2 test on Cochrane’s Q statistics and then quantified by calculating the I2. The heterogeneity test was considered statistically significant when p ≤ 0.05. In this case, the data were analysed via a random effects model. In contrast, if p > 0.05, a fixed effects model was used to analyse the data. All the statistical analyses were conducted via Stata. Sensitivity analysis and publication bias A sensitivity test was performed by sequentially excluding one study at a time and recalculating the summary effect size to examine the stability of the analysis. To verify whether publication bias might influence the validity of the incidence, a linear regression method was used. All p values were two-sided, and the cut-off for statistical significance was set at 0.05. Results Literature search A total of 495 articles were retrieved via our search strategy, and 30 records were discarded owing to duplication. The titles and abstracts of the remaining 465 articles were screened. We excluded 354 articles and retained the remaining 111 articles for further evaluation by reading the full texts. Eleven reports were not retrieved. Therefore, a total of 100 reports were assessed for eligibility. Among them, 44 reports were excluded (9 reviews, 14 with no data, 24 with insufficient data) owing to the reasons mentioned in the Table. Thus, 53 eligible articles were ultimately included in this study. Characteristics of the included studies The characteristics of the included studies are shown in Table 1. Pooled genotype proportion and allele frequency The most prevalent APOE genotype was ε3/ε3 (73.7%), followed by ε3/ε4 (14%), ε2/ε3 (7.5%), ε2/ε4 (0.785%), ε4/ε4 (0.764%), and ε2/ε2 (0.35%). The pooled genotype proportions and allele frequencies along with heterogeneity and publication bias are shown in Table 2. Pooled OR results for the meta-analysis of APOE polymorphisms and disease risk The odds ratios (ORs) and 95% confidence intervals (95% CIs) for each genotype for representative outcomes from each distinct disease are presented as forest plots in Figure 2 for neurodegenerative disorders, Figure 3 for movement disorders, Figure 4 for cognitive and mental health disorders, Figure 5 for cardiovascular disorders, Figure 6 for metabolic disorders. Compared with ε3/ε3, ε3/ε4 was associated with increased odds of 5 diseases, and ε4/ε4 was associated with increased odds of 4 diseases. The odds of 2 diseases were elevated in the presence of the ε2/ε4 genotype. ε2/ε3 was associated with decreased odds of AD. The details of the test-of-association value (p value) are provided in S1_Appendix. Genotype-Specific Disease Associations Across the included studies, the ε3/ε3 genotype was the most prevalent (73.7%) in South Asian populations, followed by ε3/ε4 (14%), ε2/ε3 (7.5%), ε2/ε4 (0.785%), ε4/ε4 (0.764%), and ε2/ε2 (0.35%). However, genotypes containing the ε4 allele, particularly ε3/ε4 and ε4/ε4, demonstrated significantly elevated odds ratios (ORs) for multiple disease categories. Neurodegenerative Disorders In the context of neurodegenerative disorders, the ApoE ε3/ε4 genotype demonstrated a significantly elevated risk for Alzheimer’s disease (AD) (z = 5.45, p < 0.001; I² = 80.09%), while ε4/ε4 was also strongly associated (z = 4.13, p < 0.001; I² = 52.92%). A weaker but still significant risk was observed with the ε2/ε4 genotype (z = 2.06, p = 0.04), whereas ε2/ε3 suggested a protective trend, though this did not reach statistical significance. For vascular dementia (VaD), both ε3/ε4 and ε4/ε4 genotypes were significantly associated with increased risk (z = 3.07 and z = 2.81, respectively; both p < 0.001), underscoring the critical role of the ε4 allele in cerebrovascular cognitive decline. In contrast, dementia with Lewy bodies (DLB) showed only a non-significant potential association with the ε4/ε4 genotype (z = 1.67, p = 0.1), while frontotemporal dementia (FTD) exhibited no significant associations with any ApoE genotype, suggesting a limited role for ApoE polymorphisms in its pathogenesis. Movement Disorders In movement disorders, the ε3/ε4 genotype showed a very strong and statistically significant association with Parkinson’s disease (PD), indicating high susceptibility among carriers (z = 5.85, p < 0.001; I² = 0%). In contrast, no ApoE genotype exhibited a statistically significant association with traumatic brain injury (TBI), suggesting a limited role of ApoE polymorphisms in TBI risk. Cognitive and Mental Health Disorders In cognitive and mental health disorders, the ε3/ε4 genotype showed a significant association with mild cognitive impairment (MCI) (z = 2.97, p < 0.001), indicating an increased risk for preclinical cognitive decline among carriers. Conversely, no significant associations were observed between any ApoE genotype and depression, including ε4/ε4 (z = 0.33, p = 0.74), although global literature suggests that the ε2 allele may have potential protective effects, a trend not statistically evident in this analysis. Cardiovascular Disorders In cardiovascular disorders, the ε3/ε4 genotype showed a strong and statistically significant association with coronary artery disease (CAD) (z = 3.16, p < 0.001), while the ε4/ε4 genotype demonstrated an elevated odds ratio that did not reach statistical significance (z = 1.69, p = 0.09). Genotypes containing the ε2 allele did not exhibit any significant associations with CAD. In contrast, the ε2/ε4 genotype was significantly associated with stroke (z = 3.09, p < 0.001; I² = 0%), suggesting a potential genetic contribution to ischemic stroke susceptibility. Metabolic Disorders In metabolic disorders, no ApoE genotype showed a significant association with diabetes mellitus (DM), including ε4/ε4, which was not significantly linked (z = -0.04, p = 0.97). However, ε4/ε4 was significantly associated with dyslipidemia (z = 2.61, p = 0.01), indicating a higher risk of lipid abnormalities, and also showed a significant positive association with obesity (z = 2.44, p = 0.01), suggesting increased susceptibility. No statistically significant genotype-disease relationships were identified for metabolic syndrome (MS), reflecting a limited role of ApoE polymorphisms in this condition within the studied population. Cross-Disease Patterns and Comparative Findings The ε4/ε4 genotype emerged as the strongest risk factor across a range of conditions, including Alzheimer’s disease (AD), vascular dementia (VaD), dyslipidemia, and obesity, highlighting its broad pathogenic potential in both neurodegenerative and metabolic domains. The ε3/ε4 genotype was consistently associated with increased risk in multiple disorders—AD, VaD, Parkinson’s disease (PD), mild cognitive impairment (MCI), and coronary artery disease (CAD)—underscoring its importance as a high-risk heterozygous variant. In contrast, the ε2/ε3 genotype appeared to be notably protective, especially against AD, and was not significantly associated with increased risk in any of the studied diseases, suggesting a possible neuroprotective and cardioprotective role. Meanwhile, the ε2/ε4 genotype demonstrated disease-specific effects, showing a significant association only with stroke, but not with other health conditions included in this analysis. Discussion This meta-analysis provides one of the most comprehensive assessments to date of the distribution and health implications of ApoE polymorphisms in South Asian populations. Our findings confirm several globally recognized genotype-disease associations while also highlighting notable regional distinctions. The ε3/ε3 genotype is the most prevalent among South Asians, accounting for 73.7% of the population, which aligns with global distribution patterns. Genotypes containing the ε4 allele, particularly ε3/ε4 and ε4/ε4, are consistently associated with an increased risk for a variety of health conditions, including neurodegenerative, cardiovascular, and metabolic disorders. In contrast, the ε2/ε3 genotype frequently demonstrates a protective effect against certain diseases, although this association does not always reach statistical significance. Neurodegenerative Diseases (AD, VaD, DLB, FTD) APOE ε4-containing genotypes (ε3/ε4 and ε4/ε4) consistently increased the risk of Alzheimer’s Disease (AD) and Vascular Dementia (VaD) in South Asian populations, aligning with global patterns of ε4-associated neurodegenerative risk. The strong association of these genotypes with AD in our meta-analysis is consistent with findings by Agarwal et al. (2014)[23], who demonstrated that while the ε4 allele is a major risk factor for AD, its lower frequency in the Indian population may contribute to the comparatively lower prevalence of AD in South Asia. Similarly, the ε4 genotype was significantly associated with increased susceptibility to VaD, aligning with the results of Yin et al. (2012)[24], who reported a robust link between ε4 and VaD risk across Asian populations. Although our analysis did not find a statistically significant association with Dementia with Lewy Bodies (DLB), the observed trend in ε4/ε4 carriers is supported by Shigemizu et al. (2022)[24], who suggested a possible role of ε4 in DLB pathogenesis, particularly in Asian cohorts. In contrast, no APOE genotype was significantly linked to Frontotemporal Dementia (FTD), reinforcing the idea that APOE polymorphisms are not major contributors to FTD risk in South Asians, as also suggested by Su et al. (2017)[25] in their updated meta-analysis. Movement Disorders (PD, TBI) The APOE ε3/ε4 genotype was significantly associated with an increased risk of Parkinson’s Disease (PD) in South Asian populations, with our meta-analysis indicating a high level of significance (z = 5.85, p < 0.001), and no observed heterogeneity (I² = 0%). This finding is consistent with the results of Sun et al. (2019)[26], who reported that the ε4 allele was associated with an elevated risk of PD in Asian cohorts, highlighting the potential of APOE ε4 as a susceptibility marker for PD beyond Alzheimer’s disease. Conversely, no APOE genotype showed a statistically significant association with Traumatic Brain Injury (TBI), including ε4/ε4, which showed a non-significant effect (z = -0.31, p = 0.75). These results align with prior findings suggesting that while APOE ε4 may influence post-injury outcomes, it does not independently confer a significant predisposition to TBI risk, as observed in broader populations (Li et al., 2018)[27]. Overall, these findings suggest a genotype-specific role for APOE ε4 in Parkinson’s Disease but not in the initial susceptibility to Traumatic Brain Injury within South Asian populations. Cognitive and Mental Health Disorders (MCI, Depression) The APOE ε3/ε4 genotype was significantly associated with increased susceptibility to Mild Cognitive Impairment (MCI) in South Asian populations. This finding is in line with the meta-analysis by Jiang et al. (2017)[28], which showed that the ε4 allele was consistently linked to elevated MCI risk across Asian cohorts, reinforcing its role as an early marker of cognitive decline. In contrast, no APOE genotype demonstrated a significant association with depression in our analysis. This is supported by Banning et al. (2019)[29], who conducted a systematic review and meta-analysis and concluded that there was no consistent evidence linking APOE ε4 to affective symptoms in individuals with MCI or Alzheimer’s disease. These results suggest that while APOE ε4 may influence early cognitive deterioration, its role in mood-related disorders such as depression remains unclear, particularly within South Asian populations. Cardiovascular Disorders (CAD, Stroke) The APOE ε3/ε4 genotype was significantly associated with an increased risk of Coronary Artery Disease (CAD) in South Asian populations, supporting its role as a genetic susceptibility factor. This finding is consistent with the meta-analysis by Xu et al. (2016)[30], which reported that individuals carrying the ε4 allele have a substantially greater risk of developing CAD, a trend observed across diverse populations, including those in Asia. In our analysis, the ε4/ε4 genotype also showed a positive but less robust association with CAD. Regarding stroke, the ε2/ε4 genotype was found to be significantly associated with increased susceptibility, particularly aligning with findings from Qiao et al. (2022)[31], who demonstrated that APOE ε4 carriers have a heightened risk of ischemic stroke, especially for the small artery disease subtype. These results reinforce the importance of APOE ε4-related genotypes in cardiovascular pathology and suggest potential avenues for early genetic risk assessment in South Asian populations. Metabolic Disorders (DM, Dyslipidaemia, Obesity, MS) Among the metabolic conditions assessed, the APOE ε4/ε4 genotype was significantly associated with dyslipidemia and obesity in South Asian populations. Our findings align with those of Anthopoulos et al. (2010)[32], who demonstrated that the ε4 allele plays a key role in altering lipid metabolism and increasing susceptibility to dyslipidemic profiles, thereby raising cardiovascular risk. Similarly, Palmer et al. (2021)[33] identified the APOE ε4 genotype as one of several active genetic contributors to obesity, influencing metabolic outcomes and lipid regulation. However, in our analysis, no APOE genotype showed a significant association with Diabetes Mellitus (DM), which contrasts with global meta-analyses such as Wu et al. (2022)[34], where ε4 was modestly associated with higher atherogenic lipid profiles in diabetic patients. Likewise, no significant association was found between APOE variants and Metabolic Syndrome (MS) in our study, suggesting that while APOE ε4 may influence specific metabolic traits, its overall role in composite metabolic disorders like DM and MS remains less clear in South Asian cohorts. The strengths of this meta-analysis are especially important because it focuses on the relatively underrepresented South Asian region in genetic studies. The systematic inclusion of 53 eligible studies across diverse health outcomes, such as cardiovascular diseases, neurodegenerative disorders, and metabolic conditions, offers a robust and comprehensive perspective on ApoE polymorphisms in this population. This analysis will, therefore, contribute significantly to filling an important knowledge gap and will add region-specific insights that could be translated into improved public health strategies and personalized medicine for South Asians. The approach taken herein to examine many genotype‒disease relationships and to use a large dataset will enhance validity. The broad category of review, including observational, case‒control, and cohort studies, further strengthens the meta-analysis, while the extensive search strategy ensures that the included studies cover a wide array of outcomes linked to ApoE polymorphisms. Despite these strengths, various limitations should be considered both at the study and review levels. At the study level, variability in design, sample size, and methodologies across included studies promotes high heterogeneity, with an I² value in some cases exceeding 80%, for instance, which may affect the consistency of the results. The small sample sizes in some studies may also potentially be a limiting factor for generalizing the findings. The incomplete retrieval of 11 identified studies adds another layer of limitation, perhaps to the comprehensiveness of the evidence base. Moreover, there is a possibility of publication bias, as was suggested by a nonparametric trim and fill analysis, which suggests that nonsignificant findings are probably underreported, therefore resulting in a biased overall result. In addition, the inadequacy of enough data from few countries in South Asia, namely, Bangladesh, Nepal, and Sri Lanka, adds to the fact that further large-scale high-quality studies need to be accomplished to understand the genetic scenario of the ApoE polymorphisms and their disease associations in this region. Declarations Author Contribution Prayash Paudel is PP1, Asutosh Sah is AS and Poonam Paudel is PP2PP1 designed and supervised the study. PP1, AS and PP2 contributed equally to the data collection, analysis, figures and manuscript preparation. All authors reviewed and approved the final manuscript. Data Availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Lumsden AL, Mulugeta A, Zhou A, Hyppönen E. Apolipoprotein E (APOE) genotype-associated disease risks: a phenome-wide, registry-based, case-control study utilising the UK Biobank. EBioMedicine 2020;59:102954. https://doi.org/10.1016/j.ebiom.2020.102954. RALL SC, MAHLEY RW. The role of apolipoprotein E genetic variants in lipoprotein disorders. J Intern Med 1992;231:653–9. https://doi.org/10.1111/j.1365-2796.1992.tb01254.x. Bu G. Apolipoprotein E and its receptors in Alzheimer’s disease: pathways, pathogenesis and therapy. Nat Rev Neurosci 2009;10:333–44. https://doi.org/10.1038/nrn2620. Eichner JE. Apolipoprotein E Polymorphism and Cardiovascular Disease: A HuGE Review. 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Tables Table 1 Characteristics of Included Studies S.N Author Year Country Sample Size Male % Mean Age Co-morbidities 1 Afaq et al. 2023 1 Pakistan 69 66 Calcific Aortic Stenosis 2 Afroze et al. 2016 2 India 450 57.77 Coronary Artery Disease 3 Agarwal et al. 2008 3 India 278 Obesity 4 Ahmed et al. 2006 4 Bangladesh 53 71.69811 5 Ali et al. 2016 5 Pakistan 90 39.7±3.5 Coronary Artery Disease 6 Asghar et al. 2013 6 India 90 7 Azhuvalappil et al. 2024 7 India 299 57.53 62.71 ± 10.13 Metabolic Syndrome 8 Azhuvalappil et al. 2024 8 India 2297 49.63 Metabolic Syndrome 9 Balgir et al. 2003 9 India 165 6.060606 17-30 10 Bazrgar et al. 2008 10 Iran 198 47.97 23.7 ± 5.2 11 Bharath et al. 2011 11 India 195 61.54 64.8 ± 7.7 Alzhemier's Disease, Vascular Dementia Other Dementia 12 Biswas et al. 2013 12 India 150 86 52.76 ± 10.16 Coronary Artery Disease 13 Chakraborty et al. 1998 13 India 162 59.25926 65 ± 9.63 Alzheimer's Disease 14 Chandak 2002 14 India 100 73.3 ± 8.3 Alzheimer's Disease, Vascular Dementia 15 Cheema et al. 2017 15 Pakistan 100 Coronary Artery Disease 16 Chhabra et al. 2000 16 India 122 47±11 17 Chowdhury et. al. 2001 17 Bangladesh 190 Stroke 18 Das et al. 2009 18 India 0 Dyslipidemia 19 Das et al. 2016 19 India 620 69.03 49.1 ± 16.9 Stroke 20 Das et al. 2008 20 India 29 Dyslipidaemia 21 Sadhukhan et al. 2023 21 India 256 67.96875 Mild cognitive impairment, Parkison’s Disease, Dementia with Lewy body, Frontotemporal dementia, Alzheimer’s disease 22 Dixit et al. 2005 22 India 264 43.93 47.37 ± 16.66 Diabetes Mellitus 23 Ganaie et al. 2020 23 India 108 68 56.1 (30-85±10.8) Stroke 24 Gupta et al. 2018 24 India 89 58 27.97 ± 4.07 25 Jairani et al. 2016 25 India 138 54 68.7 ± 8.2 Dementia 26 Kapur et al. 2006 26 India 46 27 Kaur et al. 2006 27 36 44.44444 28 Kota et al. 2012 28 India 193 59.06736 60.35 ± 15.65 Alzheimer's Disease 29 Kumar et al. 2003 29 India 45 93.33 36.4 ± 4.9 Coronary Artery Disease 30 Kumar et al. 2012 30 195 31 Luthra et al. 2004 31 India 76 63.2 ± 9.6 Alzheimer's Disease, Vascular Dementia 32 Mansoori et al. 2011 32 India 113 63.71 64.0 ± 8.4 Alzheimer's Disease and Vascular Dementia 33 Meena et al. 2011 33 India 352 46.86 35.16 ± 9.56 Dyslipidemia 34 Misra et al. 2019 (Misra et al., 2019) India 32 81.25 67.2 ± 6.5 Alzheimer's Disease, Vascular Dementia, Depression 35 Murry et al. 2011 35 India 112 36 Pal et al. 2019 36 India 302 47.9±8.5 Parkinson's Disease 37 Pandey et al. 2007 37 India 162 60.95 8 8.5 Alzheimer's Disease, Vascular Dementia 38 Periyasamy et al. 2017 38 India 184 33.15508 59.99 ± 10.44 39 Rahman et al. 2023 39 Pakistan 100 63 56.63 ± 11.87 Coronary Artery Disease 40 Ranjith et al. 2009 40 india 145 Metabolic Syndrome 41 Rastogi et al. 2018 41 India 100 65 18-73 Deep Vein Thrombosis 42 Roy et al. (2018) 42 India 291 75.6 Wilson's disease 43 Sapkota et al. 2015 43 India 1608 54.72637 50.0 ± 14.5 Diabetes Mellitus, Coronary Artery Disease 44 Seet et al. 2003 44 India 28 45 Silva et al. 2003 45 Srilanka 21 Alzheimer's Disease 46 Singh et al. 2001 46 India 150 47 Singh et al. 2006 47 India 497 48 Singh et al. 2006 48 India 97 52.10 ± 12.67 Diabetes Mellitus 49 Srivastava et al. 2016 49 India 300 Obseity 50 Tanguturi et al. 2012 50 South Asia 210 87.61905 61.3±4.6 Coronary Artery Disease 51 Thelma et al. 2001 51 India 4450 52.04494 52 Wozniak et al. 2009 52 Indian subcontinent 75 Pulmonary TB 53 Yousuf et al. 2015 53 India 450 Traumatic Brain Injury References for Table 1 1. Afaq, E. et al. Apolipoprotein E Polymorphism And Dyslipidemia In Elderly Patients Of Calcific Aortic Stenosis. Journal of Rawalpindi Medical College 27, (2023). 2. Afroze, D., Yousuf, A., Tramboo, N. A., Shah, Z. A. & Ahmad, A. 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Table 2 Pooled proportion of genotype and allele frequency in general population Genotype Pooled proportion in % (95% CI) Heterogeneity p value Publication Bias I 2 P value APOE ε2/ε2 0.35 (0.2, 0.5) 15.07 0.012 <0.001 APOE ε2/ε3 7.5 (6.6, 8.4) 72.2 <0.001 <0.001 APOE ε2/ε4 0.785 (0.6, 1) 54.8 <0.001 <0.001 APOE ε3/ε3 73.7 (71.3, 76) 90.57 <0.001 <0.001 APOE ε3/ε4 14 (12.1, 15.9) 91.36 <0.001 <0.001 APOE ε4/ε4 0.764 (0.6, 1) 33.77 0.062 <0.001 Allele Pooled Frequency (95% CI) Heterogeneity P value Publication Bias I 2 P value APOE ε2 0.0529 (0.045, 0.06) 89.58 <0.001 <0.001 APOE ε3 0.851 (0.838, 0.865) 92.16 <0.001 <0.001 APOE ε4 0.0885 (0.079, 0.098) 88.16 <0.001 <0.001 Additional Declarations No competing interests reported. Supplementary Files S1Appendix.docx S2Appendix.docx S3Appendix.docx S4Appendix.docx S5Appendix.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5554316","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":477262728,"identity":"0c42b9d4-c66e-4d12-80fa-c93b6d491755","order_by":0,"name":"Prayash Paudel","email":"data:image/png;base64,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","orcid":"","institution":"Tribhuvan University Teaching Hospital","correspondingAuthor":true,"prefix":"","firstName":"Prayash","middleName":"","lastName":"Paudel","suffix":""},{"id":477262729,"identity":"bbd07cd7-a152-4411-af25-4047b11f7ad5","order_by":1,"name":"Asutosh Sah","email":"","orcid":"","institution":"Tribhuvan University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Asutosh","middleName":"","lastName":"Sah","suffix":""},{"id":477262730,"identity":"5f0684c0-a755-476e-9ece-4c68887df594","order_by":2,"name":"Poonam Paudel","email":"","orcid":"","institution":"Pokhara University","correspondingAuthor":false,"prefix":"","firstName":"Poonam","middleName":"","lastName":"Paudel","suffix":""}],"badges":[],"createdAt":"2024-11-30 12:23:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5554316/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5554316/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85822613,"identity":"e24df9c5-7258-4544-9b49-6593fd5f21dc","added_by":"auto","created_at":"2025-07-02 06:49:53","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":214330,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePRISMA 2020 flow diagram for new systematic reviews which included searches of databases and registers only.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/b38998b5c6955c2da3153ebf.jpg"},{"id":85824170,"identity":"6c715a6a-3f72-4e59-9b32-401a02df308b","added_by":"auto","created_at":"2025-07-02 06:57:53","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":147871,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing the log odds ratios (logOR) and 95% confidence intervals (CIs) of various ApoE genotypes (e2/2, e2/3, e2/4, e3/4, e4/4) in neurodegenerative disorders, with e3/3 as the reference genotype. The plot highlights the relative risk of each genotype in relation to the e3/3 genotype, providing insights into the association of ApoE polymorphisms with a. Alzheimer’s disease b. Vascular dementia c. Dementia with lewy bodies d. Fronto temporal dementia.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/06f521aedbad50c9e301369a.jpg"},{"id":85822616,"identity":"1c80d6f8-9520-4e11-8e3f-adb3ae61988e","added_by":"auto","created_at":"2025-07-02 06:49:53","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":77291,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing the log odds ratios (logOR) and 95% confidence intervals (CIs) of various ApoE genotypes (e2/2, e2/3, e2/4, e3/4, e4/4) in Movement disorders, with e3/3 as the reference genotype. The plot highlights the relative risk of each genotype in relation to the e3/3 genotype, providing insights into the association of ApoE polymorphisms with a. Parkinson’s disease, b. Traumatic brain injury\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/7836f0d14c7276936c70b429.jpg"},{"id":85824174,"identity":"4bae3ba3-49ee-46c8-bfe4-567422f9177e","added_by":"auto","created_at":"2025-07-02 06:57:53","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":133196,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing the log odds ratios (logOR) and 95% confidence intervals (CIs) of various ApoE genotypes (e2/2, e2/3, e2/4, e3/4, e4/4) in cognitive and mental health disorder, with e3/3 as the reference genotype. The plot highlights the relative risk of each genotype in relation to the e3/3 genotype, providing insights into the association of ApoE polymorphisms with a. depression, b. mild cognitive impairment\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/54093827508142ccc5128106.jpg"},{"id":85824968,"identity":"40988bf2-b0da-415e-910e-86a5bb5dd5b4","added_by":"auto","created_at":"2025-07-02 07:05:53","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":74787,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing the log odds ratios (logOR) and 95% confidence intervals (CIs) of various ApoE genotypes (e2/2, e2/3, e2/4, e3/4, e4/4) in cardiovascular disorder, with e3/3 as the reference genotype. The plot highlights the relative risk of each genotype in relation to the e3/3 genotype, providing insights into the association of ApoE polymorphisms with a. coronary artery disease b. stroke.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/388f2d2be9257effad628b87.jpg"},{"id":85824180,"identity":"c3725722-00c8-424d-92d8-4bb484664276","added_by":"auto","created_at":"2025-07-02 06:57:53","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":179801,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing the log odds ratios (logOR) and 95% confidence intervals (CIs) of various ApoE genotypes (e2/2, e2/3, e2/4, e3/4, e4/4) in metabolic disorder, with e3/3 as the reference genotype. The plot highlights the relative risk of each genotype in relation to the e3/3 genotype, providing insights into the association of ApoE polymorphisms with a. Diabetes mellitus b. metabolic syndrome c. obesity d. dyslipidemia\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/6ff8306fa936b77627fccac9.jpg"},{"id":85827097,"identity":"cd194fb3-8e1f-4101-86fb-cb2258434d2c","added_by":"auto","created_at":"2025-07-02 07:21:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2014501,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/3ebd5b5a-e0c2-4a74-933d-bd43936be52b.pdf"},{"id":85824961,"identity":"7c78dac9-7a2e-455f-a4c2-ec0bcb25c474","added_by":"auto","created_at":"2025-07-02 07:05:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15183,"visible":true,"origin":"","legend":"","description":"","filename":"S1Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/40007b4262c8e3608f662b0b.docx"},{"id":85826320,"identity":"c7100f20-c310-4060-83db-cef84f4127e1","added_by":"auto","created_at":"2025-07-02 07:13:53","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13013,"visible":true,"origin":"","legend":"","description":"","filename":"S2Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/a06f1f63354dfb732a9a138c.docx"},{"id":85822623,"identity":"a1a7651f-cecd-41da-a306-df7cf48e77b1","added_by":"auto","created_at":"2025-07-02 06:49:53","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":34152,"visible":true,"origin":"","legend":"","description":"","filename":"S3Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/8203cdabea669a0f67758b31.docx"},{"id":85824172,"identity":"6ef1f747-b108-4ff1-9713-a847bb0c8c38","added_by":"auto","created_at":"2025-07-02 06:57:53","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":32367,"visible":true,"origin":"","legend":"","description":"","filename":"S4Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/2b1d23d1a859991b5b51dc65.docx"},{"id":85824177,"identity":"32381bbb-1a32-45f9-92b1-183776d6f5aa","added_by":"auto","created_at":"2025-07-02 06:57:53","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":26287,"visible":true,"origin":"","legend":"","description":"","filename":"S5Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5554316/v1/0543a6fe7b444513136c197c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"ApoE Polymorphism Analysis in Health and Disease of South Asian Populations","fulltext":[{"header":"Introduction","content":"\u003cp\u003eApolipoprotein E is a glycoprotein that plays a critical role in the regulation of cholesterol homeostasis and lipid metabolic processes. Mainly, it is produced by hepatocytes and astrocytes and is expressed in plasma and cerebrospinal fluid[1]. The three most common polymorphisms, which are products of three alleles (\u0026epsilon;2, \u0026epsilon;3 and \u0026epsilon;4) at a single gene locus, are E2, E3 and E4[2]. As reviewed by [3], the \u0026epsilon;3 allele is the most common allele, occurring in ~77% of the general population, whereas the \u0026epsilon;2 allele accounts for ~8%, and the \u0026epsilon;4 allele accounts for ~15%. ApoE3 is considered the parent form, being Cys112 and Arg158, whereas apoE4 is Arg112 and Arg158, and apoE2 is Cys112 and Cys158 [2]. Overall, six phenotypes are possible, with their ranking from most to least common being E3/3, E4/3, E3/2, E4/4, E4/2, and E2/2 [4].\u003c/p\u003e\n\u003cp\u003eApoE is involved mainly in lipid metabolism, although to date, it has been revealed to be important in other processes, such as neuroprotection, antimicrobial defense, oxidative stress, and inflammation [5]. ApoE binds via its surface-exposed aromatic ring to LDL receptor family members and hence participates in cholesterol transport [6]. A linear relationship was observed between the apoE genotype (\u0026epsilon;2/\u0026epsilon;2 \u0026gt; \u0026epsilon;2/\u0026epsilon;3 \u0026gt; \u0026epsilon;2/\u0026epsilon;4 \u0026gt; \u0026epsilon;3/\u0026epsilon;3 \u0026gt; \u0026epsilon;3/\u0026epsilon;4 \u0026gt; \u0026epsilon;4/\u0026epsilon;4) and both LDL-cholesterol levels and coronary artery diseases [7]. In the vascular wall, apoE secreted by macrophages participates in cellular cholesterol efflux from the atheroma [8]. ApoE secreted by macrophages mediates cholesterol efflux, thus preventing cholesterol overload and subsequent conversion into foam cells [9]. Cullen et al. reported that apoE isoforms differentially regulate cholesterol metabolism in human monocyte-derived macrophages as follows: E2/2 \u0026gt; E3/3 \u0026cong; E4/4 [10]. APOE \u0026epsilon;2-related genotypes might be protective factors for MI, whereas \u0026epsilon;4-related genotypes (\u0026epsilon;4/\u0026epsilon;3 vs. \u0026epsilon;3/\u0026epsilon;3 and \u0026epsilon;4/\u0026epsilon;4 vs. \u0026epsilon;3/\u0026epsilon;3) could be risk factors for MI [11].\u003c/p\u003e\n\u003cp\u003eIn the brain, astrocytes represent the main supplier of apoE, which is the most abundant apolipoprotein in the cerebrospinal fluid [12]. Owing to its role in the transport of lipids, apoE performs important functions in brain homeostasis, regulating lipid and glucose metabolism and effectively preserving and remodelling neuronal signalling [13\u0026ndash;15]. In the brain, apoE is provided by astrocytes, assembled in lipoproteins and then transported to neurons where it is taken up via LDL receptor superfamily members localized on the surface of the neurons [16]. Abyadeh et al. [17] performed a meta-analysis showing the association between the APOE \u0026epsilon;4 allele and susceptibility to AD among an Iranian population, whereas APOE \u0026epsilon;3 had a protective role against this devastating disorder. No significant association was observed between APOE \u0026epsilon;2 and AD, although evidence indicating the protective role of the APOE \u0026epsilon;2 allele is available.\u003c/p\u003e\n\u003cp\u003eA meta-analysis by Yin et al. (2012) [18] with a total of 29 studies including 1763 VaD cases suggested an association between ApoE 4 mutation and increased risk of VaD.\u003c/p\u003e\n\u003cp\u003eIn the meta-analysis by Lamb et al. (1998), the \u0026epsilon;2 allele frequency in DLB was found to be rather similar to that of the control group, at 9.2% and 8.9%, respectively, and may therefore have some protective effect. The \u0026epsilon;3 allele is less common in DLB patients (55.1%) than in controls (76.2%), and only 8% of DLB patients were \u0026epsilon;4/\u0026epsilon;4 homozygotes, reflecting the lesser impact of \u0026epsilon;4 homozygosity in DLB.\u003c/p\u003e\n\u003cp\u003eA meta-analysis by Feng et al. (2015) (Feng et al., 2015) suggested that the e2/e3 genotype likely provided a protective effect against depression in the overall population. The ApoE e2 allele acts as a protective factor against depression in the Caucasian population. The e4 allele and e3/e4 genotype were associated with an increased risk of depression in patients aged 50 years or over.\u003c/p\u003e\n\u003cp\u003eThe meta-analysis of Su et al. (2017) [20] showed that the APOE \u0026epsilon;4 allele significantly increased the risk for developing frontotemporal lobar degeneration (FTLD) through all investigated genetic models: \u0026epsilon;4 vs. \u0026epsilon;3, \u0026epsilon;4 vs. \u0026epsilon;2, \u0026epsilon;4 vs. \u0026epsilon;2+\u0026epsilon;3+\u0026epsilon;4, and \u0026epsilon;4 carrier models. This finding was also confirmed in subgroup analyses in Caucasians, Italians, and patients with behavioral variant frontotemporal dementia (bvFTD). Conversely, the \u0026epsilon;2 allele of APOE was not significantly associated with FTLD in most genetic models. These findings suggest that \u0026epsilon;4, but not \u0026epsilon;2, may be a genetic risk factor for FTLD.\u003c/p\u003e\n\u003cp\u003eThe results of an analysis by Banning et al. (2019) [21] revealed that APOE \u0026epsilon;4 is related to a slightly increased incidence of MCI. Compared with noncarriers, \u0026epsilon;4 carriers presented a more pronounced decline in cognitive ability, although the effect itself was highly variable across studies and due to differences in population characteristics. In contrast, the APOE \u0026epsilon;2 allele was not significantly associated with the incidence of MCI. These findings confirmed \u0026epsilon;4 as a genetic risk factor for MCI.\u003c/p\u003e\n\u003cp\u003eSignificantly, the meta-analysis of Qiao et al. (2022) indicated that the APOE \u0026epsilon;4 allele is associated with an increased risk for IS, where \u0026epsilon;4 carriers have an increased risk compared with non\u0026epsilon;4 carriers, with a pooled OR of 1.377. The results provided evidence of a dose response, where \u0026epsilon;4/\u0026epsilon;4 homozygotes presented extremely high risk, with an OR of 1.833 compared with the \u0026epsilon;3/\u0026epsilon;3 or \u0026epsilon;3/\u0026epsilon;4 genotypes. We found that the \u0026epsilon;4 mutation was specifically linked to increased susceptibility to the small artery disease (SAD) subtype of ischaemic stroke (IS), although this mutation was not detected in patients with large artery atherosclerosis or cardio-aortic embolism. These findings suggest that APOE \u0026epsilon;4 plays a dose-dependent role in the risk of IS SAD subtype cases.\u003c/p\u003e\n\u003cp\u003eWu et al. (2022) [22] noted in their meta-analysis that the APOE \u0026epsilon;4 allele is especially associated with type 2 diabetes mellitus (T2DM) because of its relationship with lipid abnormalities. More precisely, in patients with T2DM, this \u0026epsilon;4 allele is associated with higher LDL-C and lower high-density lipoprotein cholesterol (HDL-C), thus presenting a more atherogenic lipid profile. Thus, such genetic polymorphisms may increase the risk for dyslipidemia, which in turn can lead to perturbation of metabolic equilibrium and exacerbate T2DM manifestations.\u003c/p\u003e\n\u003cp\u003eApoE polymorphisms, encompassing the \u0026epsilon;2, \u0026epsilon;3, and \u0026epsilon;4 alleles, are integral to lipid metabolism and are considered risk factors for various neurodegenerative and cardiovascular diseases. Surprisingly, however, few or no comprehensive data have been reported on the distribution of ApoE alleles and their health consequences in the context of South Asia, with rapidly increasing burdens of diseases such as Alzheimer\u0026apos;s disease, coronary artery disease, and diabetes. Since most studies on ApoE have been conducted in Western populations, whose genetic constitution and lifestyle differ substantially from those of South Asia, the region-specific effects of ApoE polymorphisms need to be understood. This meta-analysis thus becomes imperative to meet the pressing need for focused, region-specific inputs that could lead to improvements in public health strategies, personalized medicine, and preventive care in South Asian populations.\u003c/p\u003e\n\u003cp\u003eThis systematic review focuses on the determination of the distribution and health effects of the ApoE polymorphisms represented by the \u0026epsilon;2, \u0026epsilon;3, and \u0026epsilon;4 alleles in South Asian populations. In accordance with the PICOS framework, this review focuses on studies conducted on human participants of South Asian origin, with a specific focus on ApoE genetic variants. The evaluated intervention would be the presence of specific ApoE polymorphisms, expressed as alleles \u0026epsilon;2, \u0026epsilon;3, and \u0026epsilon;4. Comparisons are then made among these different genotypes regarding their associations with various health outcomes, such as cardiovascular diseases, Alzheimer\u0026apos;s disease, and other metabolic and neurodegenerative conditions. The outcomes of interest were the frequency of the alleles in South Asian populations and the associated disease risk linked to each genotype. This review covers observational studies, case‒control studies, and cohort studies to systematically evaluate the evidence concerning ApoE polymorphisms and their health effects in this regional context.\u003c/p\u003e\n\u003cp\u003eDespite the large volume of literature concerning the role of ApoE polymorphisms in different pathologies, there are certain gaps in the literature review. To date, no meta-analyses have been conducted on the associations of ApoE polymorphisms with PD, metabolic syndrome, or obesity. There is also a shortage of studies regarding the interplay between obesity and traumatic brain injury in the context of ApoE polymorphisms. These gaps indicate that further focused research is needed for a complete understanding of the implications of ApoE polymorphisms in these aspects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eStudies conducted on \u003cstrong\u003ehuman participants\u003c/strong\u003e from \u003cstrong\u003eSouth Asian countries\u003c/strong\u003e (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka).\u003c/li\u003e\n \u003cli\u003eStudies that reported on \u003cstrong\u003eApoE polymorphisms\u003c/strong\u003e (\u0026epsilon;2, \u0026epsilon;3, \u0026epsilon;4) and their \u003cstrong\u003edistribution or association with health outcomes\u003c/strong\u003e.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eObservational studies\u003c/strong\u003e (cross-sectional, case\u0026ndash;control, or cohort designs).\u003c/li\u003e\n \u003cli\u003eStudies with \u003cstrong\u003esufficient genotype/allele data\u003c/strong\u003e to allow extraction or computation of effect sizes.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eFull-text articles\u003c/strong\u003e published in \u003cstrong\u003eEnglish\u003c/strong\u003e.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eStudies not involving South Asian populations or not reporting data separately for them.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eReviews, editorials, case reports, or conference abstracts\u003c/strong\u003e.\u003c/li\u003e\n \u003cli\u003eStudies without ApoE genotype data or lacking relevant outcome associations.\u003c/li\u003e\n \u003cli\u003eArticles with \u003cstrong\u003einsufficient data\u003c/strong\u003e or \u003cstrong\u003eunavailable full texts\u003c/strong\u003e despite reasonable effort.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eDuplicate reports\u003c/strong\u003e of the same dataset (only the most complete or recent included).\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis systematic review and meta-analysis followed the principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. The PRISMA diagram detailing the selection process is shown in Figure 1.\u003c/p\u003e\n\u003cp\u003eThe study protocol was registered at PROSPERO with reference CRD42024575197 before beginning the study. The full checklist and protocol for this study are included in S4_Appendix and S5_Appendix.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSearch strategy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe PubMed, Embase and Google Scholar databases were searched up to 31 July 2024. Studies were also obtained from supplementary sources, manual searches, and other repositories. Cross-references from the published articles were manually searched to retrieve additional literature.\u003c/p\u003e\n\u003cp\u003eTo create an extensive search strategy that encompassed all fields in the records as well as Medical Subject Headings (MeSH words) for broadening the search in an advanced PubMed search, the predefined phrases were identified. For PubMed, meshes of related terms and keywords combined with Boolean operators (AND, OR) were used for the systematic identification of records. The names of South Asian countries\u0026mdash;Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka\u0026mdash;were combined with search terms. The preliminary search strategy is described in S2_Appendix. For Google Scholar, the keywords \u0026ldquo;ApoE\u0026rdquo; and \u0026ldquo;Polymorphism\u0026rdquo; were used along with each southern Asian country.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelection of studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe literature search was performed by PP and AS. The included studies were exported to Google Sheets in compatible format. Duplicate articles were screened manually. Duplicates were then recorded and removed. After removing duplicates, two independent authors, PP and AS, screened the title and abstract of every article that remained. Full-text articles were obtained for the relevant studies satisfying the inclusion criteria. The data were extracted by the two authors, PP and AS, independently. Disagreements were resolved by consulting with a third author (PP) whenever necessary.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following data were extracted from the studies: name of the author, year of publication, country of study, sample size, percentage of the male population, mean age of the population and associated comorbidities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality assessment of the studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo independent reviewers (PP and AS) conducted the quality assessment for the included studies via the Newcastle‒Ottawa Scale (NOS), adapted for cross-sectional studies. Disagreements were resolved by consulting with a third author (PP) whenever necessary. The assessment framework had a maximum score of 10, with scores of seven or higher indicating a low risk of bias. The additional methodological details can be found in supplementary material S3_Appendix.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePooled genotype proportions for six genotypes and allele frequencies for three alleles were calculated along with 95% confidence intervals (95% CI) for the general population via a random effect model with a raw proportion function. For each disease, logarithms of odds ratios (log ORs) are calculated for individual ApoE genotypes compared with the reference genotype (E3/E3). We used the e3e3 genotype as a reference since it is the most common genotype. The logarithms of the odds ratios (log ORs) and 95% confidence intervals (95% CIs) for each genotype for a representative outcome from each distinct disease are presented as forest plots. Heterogeneity was evaluated via the \u0026chi;2 test on Cochrane\u0026rsquo;s Q statistics and then quantified by calculating the I2. The heterogeneity test was considered statistically significant when p \u0026le; 0.05. In this case, the data were analysed via a random effects model. In contrast, if p \u0026gt; 0.05, a fixed effects model was used to analyse the data. All the statistical analyses were conducted via Stata.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity analysis and publication bias\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA sensitivity test was performed by sequentially excluding one study at a time and recalculating the summary effect size to examine the stability of the analysis. To verify whether publication bias might influence the validity of the incidence, a linear regression method was used. All p values were two-sided, and the cut-off for statistical significance was set at 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eLiterature search\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 495 articles were retrieved via our search strategy, and 30 records were discarded owing to duplication. The titles and abstracts of the remaining 465 articles were screened. We excluded 354 articles and retained the remaining 111 articles for further evaluation by reading the full texts. Eleven reports were not retrieved. Therefore, a total of 100 reports were assessed for eligibility. Among them, 44 reports were excluded (9 reviews, 14 with no data, 24 with insufficient data) owing to the reasons mentioned in the Table. Thus, 53 eligible articles were ultimately included in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristics of the included studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe characteristics of the included studies are shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePooled genotype proportion and allele frequency\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most prevalent APOE genotype was \u0026epsilon;3/\u0026epsilon;3 (73.7%), followed by \u0026epsilon;3/\u0026epsilon;4 (14%), \u0026epsilon;2/\u0026epsilon;3 (7.5%), \u0026epsilon;2/\u0026epsilon;4 (0.785%), \u0026epsilon;4/\u0026epsilon;4 (0.764%), and \u0026epsilon;2/\u0026epsilon;2 (0.35%). The pooled genotype proportions and allele frequencies along with heterogeneity and publication bias are shown in Table 2.\u003c/p\u003e\n\u003cp\u003ePooled OR results for the meta-analysis of APOE polymorphisms and disease risk\u003c/p\u003e\n\u003cp\u003eThe odds ratios (ORs) and 95% confidence intervals (95% CIs) for each genotype for representative outcomes from each distinct disease are presented as forest plots in Figure 2 for neurodegenerative disorders, Figure 3 for movement disorders, Figure 4 for cognitive and mental health disorders, Figure 5 for cardiovascular disorders, Figure 6 for metabolic disorders. Compared with \u0026epsilon;3/\u0026epsilon;3, \u0026epsilon;3/\u0026epsilon;4 was associated with increased odds of 5 diseases, and \u0026epsilon;4/\u0026epsilon;4 was associated with increased odds of 4 diseases. The odds of 2 diseases were elevated in the presence of the \u0026epsilon;2/\u0026epsilon;4 genotype. \u0026epsilon;2/\u0026epsilon;3 was associated with decreased odds of AD. The details of the test-of-association value (p value) are provided in S1_Appendix.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eGenotype-Specific Disease Associations\u003c/h2\u003e\n\u003cp\u003eAcross the included studies, the \u0026epsilon;3/\u0026epsilon;3 genotype was the most prevalent (73.7%) in South Asian populations, followed by \u0026epsilon;3/\u0026epsilon;4 (14%), \u0026epsilon;2/\u0026epsilon;3 (7.5%), \u0026epsilon;2/\u0026epsilon;4 (0.785%), \u0026epsilon;4/\u0026epsilon;4 (0.764%), and \u0026epsilon;2/\u0026epsilon;2 (0.35%). However, genotypes containing the \u0026epsilon;4 allele, particularly \u0026epsilon;3/\u0026epsilon;4 and \u0026epsilon;4/\u0026epsilon;4, demonstrated significantly elevated odds ratios (ORs) for multiple disease categories.\u003c/p\u003e\n\u003ch3\u003eNeurodegenerative Disorders\u003c/h3\u003e\n\u003cp\u003eIn the context of neurodegenerative disorders, the ApoE \u0026epsilon;3/\u0026epsilon;4 genotype demonstrated a significantly elevated risk for Alzheimer\u0026rsquo;s disease (AD) (z = 5.45, p \u0026lt; 0.001; I\u0026sup2;\u0026nbsp;= 80.09%), while \u0026epsilon;4/\u0026epsilon;4 was also strongly associated (z = 4.13, p \u0026lt; 0.001; I\u0026sup2;\u0026nbsp;= 52.92%). A weaker but still significant risk was observed with the \u0026epsilon;2/\u0026epsilon;4 genotype (z = 2.06, p = 0.04), whereas \u0026epsilon;2/\u0026epsilon;3 suggested a protective trend, though this did not reach statistical significance. For vascular dementia (VaD), both \u0026epsilon;3/\u0026epsilon;4 and \u0026epsilon;4/\u0026epsilon;4 genotypes were significantly associated with increased risk (z = 3.07 and z = 2.81, respectively; both p \u0026lt; 0.001), underscoring the critical role of the \u0026epsilon;4 allele in cerebrovascular cognitive decline. In contrast, dementia with Lewy bodies (DLB) showed only a non-significant potential association with the \u0026epsilon;4/\u0026epsilon;4 genotype (z = 1.67, p = 0.1), while frontotemporal dementia (FTD) exhibited no significant associations with any ApoE genotype, suggesting a limited role for ApoE polymorphisms in its pathogenesis.\u003c/p\u003e\n\u003ch3\u003eMovement Disorders\u003c/h3\u003e\n\u003cp\u003eIn movement disorders, the \u0026epsilon;3/\u0026epsilon;4 genotype showed a very strong and statistically significant association with Parkinson\u0026rsquo;s disease (PD), indicating high susceptibility among carriers (z = 5.85, p \u0026lt; 0.001; I\u0026sup2;\u0026nbsp;= 0%). In contrast, no ApoE genotype exhibited a statistically significant association with traumatic brain injury (TBI), suggesting a limited role of ApoE polymorphisms in TBI risk.\u003c/p\u003e\n\u003ch3\u003eCognitive and Mental Health Disorders\u003c/h3\u003e\n\u003cp\u003eIn cognitive and mental health disorders, the \u0026epsilon;3/\u0026epsilon;4 genotype showed a significant association with mild cognitive impairment (MCI) (z = 2.97, p \u0026lt; 0.001), indicating an increased risk for preclinical cognitive decline among carriers. Conversely, no significant associations were observed between any ApoE genotype and depression, including \u0026epsilon;4/\u0026epsilon;4 (z = 0.33, p = 0.74), although global literature suggests that the \u0026epsilon;2 allele may have potential protective effects, a trend not statistically evident in this analysis.\u003c/p\u003e\n\u003ch3\u003eCardiovascular Disorders\u003c/h3\u003e\n\u003cp\u003eIn cardiovascular disorders, the \u0026epsilon;3/\u0026epsilon;4 genotype showed a strong and statistically significant association with coronary artery disease (CAD) (z = 3.16, p \u0026lt; 0.001), while the \u0026epsilon;4/\u0026epsilon;4 genotype demonstrated an elevated odds ratio that did not reach statistical significance (z = 1.69, p = 0.09). Genotypes containing the \u0026epsilon;2 allele did not exhibit any significant associations with CAD. In contrast, the \u0026epsilon;2/\u0026epsilon;4 genotype was significantly associated with stroke (z = 3.09, p \u0026lt; 0.001; I\u0026sup2;\u0026nbsp;= 0%), suggesting a potential genetic contribution to ischemic stroke susceptibility.\u003c/p\u003e\n\u003ch3\u003eMetabolic Disorders\u003c/h3\u003e\n\u003cp\u003eIn metabolic disorders, no ApoE genotype showed a significant association with diabetes mellitus (DM), including \u0026epsilon;4/\u0026epsilon;4, which was not significantly linked (z = -0.04, p = 0.97). However, \u0026epsilon;4/\u0026epsilon;4 was significantly associated with dyslipidemia (z = 2.61, p = 0.01), indicating a higher risk of lipid abnormalities, and also showed a significant positive association with obesity (z = 2.44, p = 0.01), suggesting increased susceptibility. No statistically significant genotype-disease relationships were identified for metabolic syndrome (MS), reflecting a limited role of ApoE polymorphisms in this condition within the studied population.\u003c/p\u003e\n\u003ch2\u003eCross-Disease Patterns and Comparative Findings\u003c/h2\u003e\n\u003cp\u003eThe \u0026epsilon;4/\u0026epsilon;4 genotype emerged as the strongest risk factor across a range of conditions, including Alzheimer\u0026rsquo;s disease (AD), vascular dementia (VaD), dyslipidemia, and obesity, highlighting its broad pathogenic potential in both neurodegenerative and metabolic domains. The \u0026epsilon;3/\u0026epsilon;4 genotype was consistently associated with increased risk in multiple disorders\u0026mdash;AD, VaD, Parkinson\u0026rsquo;s disease (PD), mild cognitive impairment (MCI), and coronary artery disease (CAD)\u0026mdash;underscoring its importance as a high-risk heterozygous variant. In contrast, the \u0026epsilon;2/\u0026epsilon;3 genotype appeared to be notably protective, especially against AD, and was not significantly associated with increased risk in any of the studied diseases, suggesting a possible neuroprotective and cardioprotective role. Meanwhile, the \u0026epsilon;2/\u0026epsilon;4 genotype demonstrated disease-specific effects, showing a significant association only with stroke, but not with other health conditions included in this analysis.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis meta-analysis provides one of the most comprehensive assessments to date of the distribution and health implications of ApoE polymorphisms in South Asian populations. Our findings confirm several globally recognized genotype-disease associations while also highlighting notable regional distinctions.\u003c/p\u003e\n\u003cp\u003eThe \u0026epsilon;3/\u0026epsilon;3 genotype is the most prevalent among South Asians, accounting for 73.7% of the population, which aligns with global distribution patterns. Genotypes containing the \u0026epsilon;4 allele, particularly \u0026epsilon;3/\u0026epsilon;4 and \u0026epsilon;4/\u0026epsilon;4, are consistently associated with an increased risk for a variety of health conditions, including neurodegenerative, cardiovascular, and metabolic disorders. In contrast, the \u0026epsilon;2/\u0026epsilon;3 genotype frequently demonstrates a protective effect against certain diseases, although this association does not always reach statistical significance.\u003c/p\u003e\n\u003ch2\u003eNeurodegenerative Diseases (AD, VaD, DLB, FTD)\u003c/h2\u003e\n\u003cp\u003eAPOE \u0026epsilon;4-containing genotypes (\u0026epsilon;3/\u0026epsilon;4 and \u0026epsilon;4/\u0026epsilon;4) consistently increased the risk of Alzheimer\u0026rsquo;s Disease (AD) and Vascular Dementia (VaD) in South Asian populations, aligning with global patterns of \u0026epsilon;4-associated neurodegenerative risk. The strong association of these genotypes with AD in our meta-analysis is consistent with findings by Agarwal et al. (2014)[23], who demonstrated that while the \u0026epsilon;4 allele is a major risk factor for AD, its lower frequency in the Indian population may contribute to the comparatively lower prevalence of AD in South Asia. Similarly, the \u0026epsilon;4 genotype was significantly associated with increased susceptibility to VaD, aligning with the results of Yin et al. (2012)[24], who reported a robust link between \u0026epsilon;4 and VaD risk across Asian populations. Although our analysis did not find a statistically significant association with Dementia with Lewy Bodies (DLB), the observed trend in \u0026epsilon;4/\u0026epsilon;4 carriers is supported by Shigemizu et al. (2022)[24], who suggested a possible role of \u0026epsilon;4 in DLB pathogenesis, particularly in Asian cohorts. In contrast, no APOE genotype was significantly linked to Frontotemporal Dementia (FTD), reinforcing the idea that APOE polymorphisms are not major contributors to FTD risk in South Asians, as also suggested by Su et al. (2017)[25] in their updated meta-analysis.\u003c/p\u003e\n\u003ch2\u003eMovement Disorders (PD, TBI)\u003c/h2\u003e\n\u003cp\u003eThe APOE \u0026epsilon;3/\u0026epsilon;4 genotype was significantly associated with an increased risk of Parkinson\u0026rsquo;s Disease (PD) in South Asian populations, with our meta-analysis indicating a high level of significance (z = 5.85, p \u0026lt; 0.001), and no observed heterogeneity (I\u0026sup2;\u0026nbsp;= 0%). This finding is consistent with the results of Sun et al. (2019)[26], who reported that the \u0026epsilon;4 allele was associated with an elevated risk of PD in Asian cohorts, highlighting the potential of APOE \u0026epsilon;4 as a susceptibility marker for PD beyond Alzheimer\u0026rsquo;s disease. Conversely, no APOE genotype showed a statistically significant association with Traumatic Brain Injury (TBI), including \u0026epsilon;4/\u0026epsilon;4, which showed a non-significant effect (z = -0.31, p = 0.75). These results align with prior findings suggesting that while APOE \u0026epsilon;4 may influence post-injury outcomes, it does not independently confer a significant predisposition to TBI risk, as observed in broader populations (Li et al., 2018)[27]. Overall, these findings suggest a genotype-specific role for APOE \u0026epsilon;4 in Parkinson\u0026rsquo;s Disease but not in the initial susceptibility to Traumatic Brain Injury within South Asian populations.\u003c/p\u003e\n\u003ch2\u003eCognitive and Mental Health Disorders (MCI, Depression)\u003c/h2\u003e\n\u003cp\u003eThe APOE \u0026epsilon;3/\u0026epsilon;4 genotype was significantly associated with increased susceptibility to Mild Cognitive Impairment (MCI) in South Asian populations. This finding is in line with the meta-analysis by Jiang et al. (2017)[28], which showed that the \u0026epsilon;4 allele was consistently linked to elevated MCI risk across Asian cohorts, reinforcing its role as an early marker of cognitive decline. In contrast, no APOE genotype demonstrated a significant association with depression in our analysis. This is supported by Banning et al. (2019)[29], who conducted a systematic review and meta-analysis and concluded that there was no consistent evidence linking APOE \u0026epsilon;4 to affective symptoms in individuals with MCI or Alzheimer\u0026rsquo;s disease. These results suggest that while APOE \u0026epsilon;4 may influence early cognitive deterioration, its role in mood-related disorders such as depression remains unclear, particularly within South Asian populations.\u003c/p\u003e\n\u003ch2\u003eCardiovascular Disorders (CAD, Stroke)\u003c/h2\u003e\n\u003cp\u003eThe APOE \u0026epsilon;3/\u0026epsilon;4 genotype was significantly associated with an increased risk of Coronary Artery Disease (CAD) in South Asian populations, supporting its role as a genetic susceptibility factor. This finding is consistent with the meta-analysis by Xu et al. (2016)[30], which reported that individuals carrying the \u0026epsilon;4 allele have a substantially greater risk of developing CAD, a trend observed across diverse populations, including those in Asia. In our analysis, the \u0026epsilon;4/\u0026epsilon;4 genotype also showed a positive but less robust association with CAD. Regarding stroke, the \u0026epsilon;2/\u0026epsilon;4 genotype was found to be significantly associated with increased susceptibility, particularly aligning with findings from Qiao et al. (2022)[31], who demonstrated that APOE \u0026epsilon;4 carriers have a heightened risk of ischemic stroke, especially for the small artery disease subtype. These results reinforce the importance of APOE \u0026epsilon;4-related genotypes in cardiovascular pathology and suggest potential avenues for early genetic risk assessment in South Asian populations.\u003c/p\u003e\n\u003ch2\u003eMetabolic Disorders (DM, Dyslipidaemia, Obesity, MS)\u003c/h2\u003e\n\u003cp\u003eAmong the metabolic conditions assessed, the APOE \u0026epsilon;4/\u0026epsilon;4 genotype was significantly associated with dyslipidemia and obesity in South Asian populations. Our findings align with those of Anthopoulos et al. (2010)[32], who demonstrated that the \u0026epsilon;4 allele plays a key role in altering lipid metabolism and increasing susceptibility to dyslipidemic profiles, thereby raising cardiovascular risk. Similarly, Palmer et al. (2021)[33] identified the APOE \u0026epsilon;4 genotype as one of several active genetic contributors to obesity, influencing metabolic outcomes and lipid regulation. However, in our analysis, no APOE genotype showed a significant association with Diabetes Mellitus (DM), which contrasts with global meta-analyses such as Wu et al. (2022)[34], where \u0026epsilon;4 was modestly associated with higher atherogenic lipid profiles in diabetic patients. Likewise, no significant association was found between APOE variants and Metabolic Syndrome (MS) in our study, suggesting that while APOE \u0026epsilon;4 may influence specific metabolic traits, its overall role in composite metabolic disorders like DM and MS remains less clear in South Asian cohorts.\u003c/p\u003e\n\u003cp\u003eThe strengths of this meta-analysis are especially important because it focuses on the relatively underrepresented South Asian region in genetic studies. The systematic inclusion of 53 eligible studies across diverse health outcomes, such as cardiovascular diseases, neurodegenerative disorders, and metabolic conditions, offers a robust and comprehensive perspective on ApoE polymorphisms in this population. This analysis will, therefore, contribute significantly to filling an important knowledge gap and will add region-specific insights that could be translated into improved public health strategies and personalized medicine for South Asians. The approach taken herein to examine many genotype‒disease relationships and to use a large dataset will enhance validity. The broad category of review, including observational, case‒control, and cohort studies, further strengthens the meta-analysis, while the extensive search strategy ensures that the included studies cover a wide array of outcomes linked to ApoE polymorphisms.\u003c/p\u003e\n\u003cp\u003eDespite these strengths, various limitations should be considered both at the study and review levels. At the study level, variability in design, sample size, and methodologies across included studies promotes high heterogeneity, with an I\u0026sup2; value in some cases exceeding 80%, for instance, which may affect the consistency of the results. The small sample sizes in some studies may also potentially be a limiting factor for generalizing the findings. The incomplete retrieval of 11 identified studies adds another layer of limitation, perhaps to the comprehensiveness of the evidence base. Moreover, there is a possibility of publication bias, as was suggested by a nonparametric trim and fill analysis, which suggests that nonsignificant findings are probably underreported, therefore resulting in a biased overall result. In addition, the inadequacy of enough data from few countries in South Asia, namely, Bangladesh, Nepal, and Sri Lanka, adds to the fact that further large-scale high-quality studies need to be accomplished to understand the genetic scenario of the ApoE polymorphisms and their disease associations in this region.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePrayash Paudel is PP1, Asutosh Sah is AS and Poonam Paudel is PP2PP1 designed and supervised the study. PP1, AS and PP2 contributed equally to the data collection, analysis, figures and manuscript preparation. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLumsden AL, Mulugeta A, Zhou A, Hypp\u0026ouml;nen E. Apolipoprotein E (APOE) genotype-associated disease risks: a phenome-wide, registry-based, case-control study utilising the UK Biobank. EBioMedicine 2020;59:102954. https://doi.org/10.1016/j.ebiom.2020.102954.\u003c/li\u003e\n\u003cli\u003eRALL SC, MAHLEY RW. The role of apolipoprotein E genetic variants in lipoprotein disorders. J Intern Med 1992;231:653\u0026ndash;9. https://doi.org/10.1111/j.1365-2796.1992.tb01254.x.\u003c/li\u003e\n\u003cli\u003eBu G. Apolipoprotein E and its receptors in Alzheimer\u0026rsquo;s disease: pathways, pathogenesis and therapy. Nat Rev Neurosci 2009;10:333\u0026ndash;44. https://doi.org/10.1038/nrn2620.\u003c/li\u003e\n\u003cli\u003eEichner JE. Apolipoprotein E Polymorphism and Cardiovascular Disease: A HuGE Review. Am J Epidemiol 2002;155:487\u0026ndash;95. https://doi.org/10.1093/aje/155.6.487.\u003c/li\u003e\n\u003cli\u003eTudorache IF, Trusca VG, Gafencu AV. Apolipoprotein E - A Multifunctional Protein with Implications in Various Pathologies as a Result of Its Structural Features. Comput Struct Biotechnol J 2017;15:359\u0026ndash;65. https://doi.org/10.1016/j.csbj.2017.05.003.\u003c/li\u003e\n\u003cli\u003eGetz GS, Reardon CA. Apoprotein E as a lipid transport and signaling protein in the blood, liver, and artery wall. J Lipid Res 2009;50:S156\u0026ndash;61. https://doi.org/10.1194/jlr.R800058-JLR200.\u003c/li\u003e\n\u003cli\u003eBennet AM, Di Angelantonio E, Ye Z, Wensley F, Dahlin A, Ahlbom A, et al. Association of Apolipoprotein E Genotypes With Lipid Levels and Coronary Risk. JAMA 2007;298:1300. https://doi.org/10.1001/jama.298.11.1300.\u003c/li\u003e\n\u003cli\u003eRosenson RS, Brewer HB, Davidson WS, Fayad ZA, Fuster V, Goldstein J, et al. Cholesterol Efflux and Atheroprotection. Circulation 2012;125:1905\u0026ndash;19. https://doi.org/10.1161/CIRCULATIONAHA.111.066589.\u003c/li\u003e\n\u003cli\u003eDove DE, Linton MF, Fazio S. ApoE-mediated cholesterol efflux from macrophages: separation of autocrine and paracrine effects. American Journal of Physiology-Cell Physiology 2005;288:C586\u0026ndash;92. https://doi.org/10.1152/ajpcell.00210.2004.\u003c/li\u003e\n\u003cli\u003eCullen P, Cignarella A, Brennhausen B, Mohr S, Assmann G, von Eckardstein A. Phenotype-dependent differences in apolipoprotein E metabolism and in cholesterol homeostasis in human monocyte-derived macrophages. Journal of Clinical Investigation 1998;101:1670\u0026ndash;7. https://doi.org/10.1172/JCI119887.\u003c/li\u003e\n\u003cli\u003eShao A, Shi J, Liang Z, Pan L, Zhu W, Liu S, et al. Meta-analysis of the association between Apolipoprotein E polymorphism and risks of myocardial infarction. BMC Cardiovasc Disord 2022;22:126. https://doi.org/10.1186/s12872-022-02566-0.\u003c/li\u003e\n\u003cli\u003eBoyles JK, Pitas RE, Wilson E, Mahley RW, Taylor JM. Apolipoprotein E associated with astrocytic glia of the central nervous system and with nonmyelinating glia of the peripheral nervous system. Journal of Clinical Investigation 1985;76:1501\u0026ndash;13. https://doi.org/10.1172/JCI112130.\u003c/li\u003e\n\u003cli\u003eLiu C-C, Kanekiyo T, Xu H, Bu G. Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat Rev Neurol 2013;9:106\u0026ndash;18. https://doi.org/10.1038/nrneurol.2012.263.\u003c/li\u003e\n\u003cli\u003eHoltzman DM, Herz J, Bu G. Apolipoprotein E and Apolipoprotein E Receptors: Normal Biology and Roles in Alzheimer Disease. Cold Spring Harb Perspect Med 2012;2:a006312\u0026ndash;a006312. https://doi.org/10.1101/cshperspect.a006312.\u003c/li\u003e\n\u003cli\u003eDumitrescu M, Gafencu AV, Fuior EV. New insights on apoliprotein E involvement in brain lipid homeostasis. Rom Biotechnol Lett 2016;21:11443\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003eGee JR, Keller JN. Astrocytes: regulation of brain homeostasis via apolipoprotein E. Int J Biochem Cell Biol 2005;37:1145\u0026ndash;50. https://doi.org/10.1016/j.biocel.2004.10.004.\u003c/li\u003e\n\u003cli\u003eAbyadeh M, Djafarian K, Heydarinejad F, Alizadeh S, Shab-Bidar S. Association between Apolipoprotein E Gene Polymorphism and Alzheimer\u0026rsquo;s Disease in an Iranian Population: A Meta-Analysis. Journal of Molecular Neuroscience 2019;69:557\u0026ndash;62. https://doi.org/10.1007/s12031-019-01381-1.\u003c/li\u003e\n\u003cli\u003eYin Y-W, Li J-C, Wang J-Z, Li B-H, Pi Y, Yang Q-W, et al. Association between apolipoprotein E gene polymorphism and the risk of vascular dementia: A meta-analysis. Neurosci Lett 2012;514:6\u0026ndash;11. https://doi.org/10.1016/j.neulet.2012.02.031.\u003c/li\u003e\n\u003cli\u003eFeng F, Lu S-S, Hu C-Y, Gong F-F, Qian Z-Z, Yang H-Y, et al. Association between apolipoprotein E gene polymorphism and depression. Journal of Clinical Neuroscience 2015;22:1232\u0026ndash;8. https://doi.org/10.1016/j.jocn.2015.02.012.\u003c/li\u003e\n\u003cli\u003eSu W-H, Shi Z-H, Liu S-L, Wang X-D, Liu S, Ji Y. Oncotarget 43721 www.impactjournals.com/oncotarget Updated meta-analysis of the role of APOE \u0026epsilon;2/\u0026epsilon;3/\u0026epsilon;4 alleles in frontotemporal lobar degeneration. vol. 8. 2017.\u003c/li\u003e\n\u003cli\u003eBanning LCP, Ramakers IHGB, Deckers K, Verhey FRJ, Aalten P. Apolipoprotein E and affective symptoms in mild cognitive impairment and Alzheimer\u0026rsquo;s disease dementia: A systematic review and meta-analysis. Neurosci Biobehav Rev 2019;96:302\u0026ndash;15. https://doi.org/10.1016/j.neubiorev.2018.11.020.\u003c/li\u003e\n\u003cli\u003eWu L, Zhang Y, Zhao H, Rong G, Huang P, Wang F, et al. Dissecting the Association of Apolipoprotein E Gene Polymorphisms With Type 2 Diabetes Mellitus and Coronary Artery Disease. Front Endocrinol (Lausanne) 2022;13. https://doi.org/10.3389/fendo.2022.838547.\u003c/li\u003e\n\u003cli\u003eAgarwal R, Tripathi CB. Association of apolipoprotein e genetic variation in alzheimer\u0026rsquo;s disease in indian population: A meta-analysis. Am J Alzheimers Dis Other Demen 2014;29:575\u0026ndash;82. https://doi.org/10.1177/1533317514531443.\u003c/li\u003e\n\u003cli\u003eShigemizu D, Asanomi Y, Akiyama S, Higaki S, Sakurai T, Ito K, et al. Network-based meta-analysis and the candidate gene association studies reveal novel ethnicity-specific variants in MFSD3 and MRPL43 associated with dementia with Lewy bodies. American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics 2022;189:139\u0026ndash;50. https://doi.org/10.1002/ajmg.b.32908.\u003c/li\u003e\n\u003cli\u003eSu W-H, Shi Z-H, Liu S-L, Wang X-D, Liu S, Ji Y. Updated meta-analysis of the role of APOE \u0026epsilon;2/\u0026epsilon;3/\u0026epsilon;4 alleles in frontotemporal lobar degeneration. Oncotarget 2017;8:43721\u0026ndash;32. https://doi.org/10.18632/oncotarget.17341.\u003c/li\u003e\n\u003cli\u003eSun R, Yang S, Zheng B, Liu J, Ma X. Apolipoprotein E Polymorphisms and Parkinson Disease With or Without Dementia: A Meta-Analysis Including 6453 Participants. J Geriatr Psychiatry Neurol 2019;32:3\u0026ndash;15. https://doi.org/10.1177/0891988718813675.\u003c/li\u003e\n\u003cli\u003eLi J, Luo J, Liu L, Fu H, Tang L. The genetic association between apolipoprotein E gene polymorphism and Parkinson disease: A meta-Analysis of 47 studies. Medicine 2018;97:e12884. https://doi.org/10.1097/MD.0000000000012884.\u003c/li\u003e\n\u003cli\u003eJiang Y, He T, Deng W, Sun P. Association between apolipoprotein E gene polymorphism and mild cognitive impairment: a meta-analysis. Clin Interv Aging 2017;Volume 12:1941\u0026ndash;9. https://doi.org/10.2147/CIA.S143632.\u003c/li\u003e\n\u003cli\u003eBanning LCP, Ramakers IHGB, Deckers K, Verhey FRJ, Aalten P. Apolipoprotein E and affective symptoms in mild cognitive impairment and Alzheimer\u0026rsquo;s disease dementia: A systematic review and meta-analysis. Neurosci Biobehav Rev 2019;96:302\u0026ndash;15. https://doi.org/10.1016/j.neubiorev.2018.11.020.\u003c/li\u003e\n\u003cli\u003eXu M, Zhao J, Zhang Y, Ma X, Dai Q, Zhi H, et al. Apolipoprotein E Gene Variants and Risk of Coronary Heart Disease: A Meta-Analysis. Biomed Res Int 2016;2016:3912175. https://doi.org/10.1155/2016/3912175.\u003c/li\u003e\n\u003cli\u003eQiao S-Y, Shang K, Chu Y-H, Yu H-H, Chen X, Qin C, et al. Apolipoprotein E \u0026epsilon;4 Polymorphism as a Risk Factor for Ischemic Stroke: A Systematic Review and Meta-Analysis. Dis Markers 2022;2022:1407183. https://doi.org/10.1155/2022/1407183.\u003c/li\u003e\n\u003cli\u003eAnthopoulos PG, Hamodrakas SJ, Bagos PG. Apolipoprotein E polymorphisms and type 2 diabetes: a meta-analysis of 30 studies including 5423 cases and 8197 controls. Mol Genet Metab 2010;100:283\u0026ndash;91. https://doi.org/10.1016/j.ymgme.2010.03.008.\u003c/li\u003e\n\u003cli\u003ePalmer ND, Kahali B, Kuppa A, Chen Y, Du X, Feitosa MF, et al. Allele-specific variation at \u003cem\u003eAPOE\u003c/em\u003e increases nonalcoholic fatty liver disease and obesity but decreases risk of Alzheimer\u0026rsquo;s disease and myocardial infarction. Hum Mol Genet 2021;30:1443\u0026ndash;56. https://doi.org/10.1093/hmg/ddab096.\u003c/li\u003e\n\u003cli\u003eWu L, Zhang Y, Zhao H, Rong G, Huang P, Wang F, et al. Dissecting the Association of Apolipoprotein E Gene Polymorphisms With Type 2 Diabetes Mellitus and Coronary Artery Disease. Front Endocrinol (Lausanne) 2022;13:838547. https://doi.org/10.3389/fendo.2022.838547.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Characteristics of Included Studies\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eS.N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAuthor Year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCountry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSample Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMale %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMean Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCo-morbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAfaq et al. 2023 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePakistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCalcific Aortic Stenosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAfroze et al. 2016 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e57.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAgarwal et al. 2008 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAhmed et al. 2006 \u003csup\u003e\u003cspan lang=\"EN\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBangladesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e71.69811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAli et al. 2016 \u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePakistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e39.7\u0026plusmn;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAsghar et al. 2013 \u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAzhuvalappil et al. 2024 \u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e57.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e62.71 \u0026plusmn; 10.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMetabolic Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAzhuvalappil et al. 2024 \u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e49.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMetabolic Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBalgir et al. 2003 \u003csup\u003e\u003cspan lang=\"EN\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6.060606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e17-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBazrgar et al. 2008 \u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e47.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e23.7 \u0026plusmn; 5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBharath et al. 2011 \u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e61.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e64.8 \u0026plusmn; 7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzhemier\u0026apos;s Disease, Vascular Dementia Other Dementia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBiswas et al. 2013 \u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e52.76 \u0026plusmn; 10.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eChakraborty et al. 1998\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e59.25926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e65 \u0026plusmn; 9.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzheimer\u0026apos;s Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eChandak 2002\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e73.3 \u0026plusmn; 8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzheimer\u0026apos;s Disease, Vascular Dementia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCheema et al. 2017 \u003csup\u003e\u003cspan lang=\"EN\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePakistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eChhabra et al. 2000 \u003csup\u003e16\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e47\u0026plusmn;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eChowdhury et. al. 2001 \u003csup\u003e17\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBangladesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eStroke\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDas et al. 2009 \u003csup\u003e18\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDas et al. 2016 \u003csup\u003e19\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e69.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e49.1 \u0026plusmn; 16.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eStroke\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDas et al. 2008 \u003csup\u003e20\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDyslipidaemia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSadhukhan et al. 2023 \u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e67.96875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMild cognitive impairment, Parkison\u0026rsquo;s Disease, Dementia with Lewy body, Frontotemporal dementia,\u0026nbsp;\u003cbr\u003e\u0026nbsp;Alzheimer\u0026rsquo;s disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDixit et al. 2005 \u003csup\u003e22\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e43.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e47.37 \u0026plusmn; 16.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eGanaie et al. 2020 \u003csup\u003e23\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e56.1 (30-85\u0026plusmn;10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eStroke\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eGupta et al. 2018 \u003csup\u003e24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e27.97 \u0026plusmn; 4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eJairani et al. 2016 \u003csup\u003e25\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e68.7 \u0026plusmn; 8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eKapur et al. 2006\u003csup\u003e26\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eKaur et al. 2006\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e44.44444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eKota et al. 2012 \u003csup\u003e28\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e59.06736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e60.35 \u0026plusmn; 15.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzheimer\u0026apos;s Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eKumar et al. 2003 \u003csup\u003e29\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e93.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e36.4 \u0026plusmn; 4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eKumar et al. 2012 \u003csup\u003e30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLuthra et al. 2004 \u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e63.2 \u0026plusmn; 9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzheimer\u0026apos;s Disease, Vascular Dementia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMansoori et al. 2011 \u003csup\u003e32\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e63.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e64.0 \u0026plusmn; 8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzheimer\u0026apos;s Disease and Vascular Dementia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMeena et al. 2011 \u003csup\u003e33\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e46.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e35.16 \u0026plusmn; 9.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMisra et al. 2019 (Misra et al., 2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e81.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e67.2 \u0026plusmn; 6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzheimer\u0026apos;s Disease, Vascular Dementia, Depression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMurry et al. 2011 \u003csup\u003e35\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePal et al. 2019 \u003csup\u003e36\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e47.9\u0026plusmn;8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eParkinson\u0026apos;s Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePandey et al. 2007 \u003csup\u003e37\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e60.95 8 8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzheimer\u0026apos;s Disease, Vascular Dementia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePeriyasamy et al. 2017 \u003csup\u003e38\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e33.15508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e59.99 \u0026plusmn; 10.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRahman et al. 2023 \u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePakistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e56.63 \u0026plusmn; 11.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRanjith et al. 2009 \u003csup\u003e40\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eindia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMetabolic Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRastogi et al. 2018 \u003csup\u003e41\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e18-73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDeep Vein Thrombosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRoy et al. (2018) \u003csup\u003e42\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e75.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eWilson\u0026apos;s disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSapkota et al. 2015 \u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e54.72637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e50.0 \u0026plusmn; 14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDiabetes Mellitus, Coronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSeet et al. 2003 \u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSilva et al. 2003 \u003csup\u003e45\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSrilanka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAlzheimer\u0026apos;s Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSingh et al. 2001 \u003csup\u003e46\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSingh et al. 2006 \u003csup\u003e47\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSingh et al. 2006 \u003csup\u003e48\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e52.10 \u0026plusmn; 12.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSrivastava et al. 2016 \u003csup\u003e49\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eObseity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTanguturi et al. 2012 \u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSouth Asia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e87.61905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e61.3\u0026plusmn;4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCoronary Artery Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eThelma et al. 2001 \u003csup\u003e51\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e52.04494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eWozniak et al. 2009 \u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndian subcontinent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePulmonary TB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eYousuf et al. 2015 \u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTraumatic Brain Injury\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eReferences for Table 1\u003c/p\u003e\n\u003cp\u003e1.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Afaq, E. et al. Apolipoprotein E Polymorphism And Dyslipidemia In Elderly Patients Of Calcific Aortic Stenosis. Journal of Rawalpindi Medical College 27, (2023).\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Afroze, D., Yousuf, A., Tramboo, N. A., Shah, Z. A. \u0026amp; Ahmad, A. ApoE gene polymorphism and its relationship with coronary artery disease in ethnic Kashmiri population. Clin Exp Med 16, 551\u0026ndash;556 (2016).\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Srivastava, N. et al. Association of cholesteryl ester transfer protein (Taq IB) and apolipoprotein E (Hha I) gene variants with obesity. Mol Cell Biochem 314, 171\u0026ndash;177 (2008).\u003c/p\u003e\n\u003cp\u003e4.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Ahmed, M. U. \u0026amp; Akhteruzzaman, S. Apolipoprotein_E_Apo_E_gene_polymorphism. J. Med. Sci (2006).\u003c/p\u003e\n\u003cp\u003e5.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Ali, A., Babar, M. E., Awan, A. R., Tayyab, M. \u0026amp; Shehzad, W. Apolipoprotein-E Gene Isoforms Genetic Spectrum in Pakistani Survivors of Myocardial Infarction. Pakistan J. Zool vol. 48 http://www.socscistatistics.com (2016).\u003c/p\u003e\n\u003cp\u003e6.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Asghar, M., Kabita, S., Kalla, L., Murry, B. \u0026amp; Saraswathy, K. N. Prevalence of MTHFR, Factor V, ACE and APOE gene polymorphisms among Muslims of Manipur, India. Annals of Human Biology vol. 40 83\u0026ndash;87 Preprint at https://doi.org/10.3109/03014460.2012.737832 (2013).\u003c/p\u003e\n\u003cp\u003e7.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Azhuvalappil, S. et al. Sex-specific differences in the association between APOE genotype and metabolic syndrome among middle-aged and older rural Indians. Metabol Open 22, 100281 (2024).\u003c/p\u003e\n\u003cp\u003e8.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Azhuvalappil, S. et al. Association between APOE genotypes and metabolic syndrome in a middle aged and elderly Urban South Indian population. Metabol Open 23, 100301 (2024).\u003c/p\u003e\n\u003cp\u003e9.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Balgir, P. P. \u0026amp; Kaur, M. Restriction Isotyping of Apolipoprotein E among Populations of Punjab, Northwestern India. Hum Biol 75, 771\u0026ndash;776 (2003).\u003c/p\u003e\n\u003cp\u003e10.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Bazrgar, M. et al. Apolipoprotein E polymorphism in Southern Iran: E4 allele in the lowest reported amounts. Mol Biol Rep 35, 495\u0026ndash;499 (2008).\u003c/p\u003e\n\u003cp\u003e11.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Bharath, S. et al. Apolipoprotein E Polymorphism and Dementia: A Hospital-Based Study from Southern India. Dement Geriatr Cogn Disord 30, 455\u0026ndash;460 (2010).\u003c/p\u003e\n\u003cp\u003e12.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Biswas, S. et al. Apolipoproteins AI/B/E gene polymorphism and their plasma levels in patients with coronary artery disease in a tertiary care-center of Eastern India. Indian Heart J 65, 658\u0026ndash;665 (2013).\u003c/p\u003e\n\u003cp\u003e13.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Mastana, S. S., Calderon, R., Pena, J., Reddy, P. H. \u0026amp; Papiha, S. S. Anthropology of the apolipoprotein E (apo E) gene: low frequency of apo E4 allele in Basques and in tribal (Baiga) populations of India. Ann Hum Biol 25, 137\u0026ndash;143 (1998).\u003c/p\u003e\n\u003cp\u003e14.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Chandak, G. R., Sridevi, M. U., Vas, C. J., Panikker, D. M. \u0026amp; Singh, L. Apolipoprotein E and Presenilin-1 Allelic Variation and Alzheimer\u0026rsquo;s Disease in India. Hum Biol 74, 683\u0026ndash;693 (2002).\u003c/p\u003e\n\u003cp\u003e15.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Cheema, A. N. \u0026amp; Bhatti, A. Screening of Candidate Coronary Artery Disease Genes in Pakistani Population. (2017).\u003c/p\u003e\n\u003cp\u003e16.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Chhabra, S. et al. Study of Apolipoprotein E Polymorphism in Normal Healthy Controls from Northern India.\u003c/p\u003e\n\u003cp\u003e17.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Chowdhury, A. H. et al. Apolipoprotein E Genetic Polymorphism and Stroke Subtypes in a Bangladeshi Hospital-Based Study. Journal of Epidemiology vol. 11.\u003c/p\u003e\n\u003cp\u003e18.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Das, M., Pal, S. \u0026amp; Ghosh, A. Synergistic effects of ACE (I/D) and ApoE (HhaI) gene polymorphisms among the adult Asian Indians with and without metabolic syndrome. Diabetes Res Clin Pract 86, (2009).\u003c/p\u003e\n\u003cp\u003e19.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Das, S., Kaul, S., Jyothy, A. \u0026amp; Munshi, A. Association of APOE (E2, E3 and E4) gene variants and lipid levels in ischemic stroke, its subtypes and hemorrhagic stroke in a South Indian population. Neurosci Lett 628, 136\u0026ndash;141 (2016).\u003c/p\u003e\n\u003cp\u003e20.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Das, M., Pal, S. \u0026amp; Ghosh, A. Apolipoprotein E gene polymorphism and dyslipidaemia in adult Asian Indians: A population based study from Calcutta, India. Indian J Hum Genet 14, 87\u0026ndash;91 (2008).\u003c/p\u003e\n\u003cp\u003e21.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sadhukhan, D. et al. Evaluation of Apolipoprotein e4 allele as susceptible factor for neurodegenerative diseases among Eastern Indians. Preprint at https://doi.org/10.1101/2023.06.21.23291697 (2023).\u003c/p\u003e\n\u003cp\u003e22.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Dixit, M., Bhattacharya, S. \u0026amp; Mittal, B. Association of CETP TaqI and APOE polymorphisms with type II diabetes mellitus in North Indians: a case control study. BMC Endocr Disord 5, 7 (2005).\u003c/p\u003e\n\u003cp\u003e23.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Ganaie, H. et al. Association of APOE gene polymorphism with stroke patients from rural Eastern India. Ann Indian Acad Neurol 23, 504 (2020).\u003c/p\u003e\n\u003cp\u003e24.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Gupta, M. D. et al. Role of ApoE gene polymorphism and nonconventional biochemical risk factors among very young individuals (aged less than 35 years) presenting with acute myocardial infarction. Indian Heart J 70, S146\u0026ndash;S156 (2018).\u003c/p\u003e\n\u003cp\u003e25.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Jairani, P. S., Aswathy, P. M., Gopala, S., Verghese, J. \u0026amp; Mathuranath, P. S. Interaction with the MAPT H1H1 Genotype Increases Dementia Risk in APOE \u0026epsilon;4 Carriers in a Population of Southern India. Dement Geriatr Cogn Disord 42, 255\u0026ndash;264 (2016).\u003c/p\u003e\n\u003cp\u003e26.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sharad, S., Kapoor, M. \u0026amp; Bala, K. ApoE Genotypes : Risk factor for Alzheimer \u0026rsquo; s Disease. Journal of Indian Academy of Clinical Medicine 7, 118\u0026ndash;122 (2006).\u003c/p\u003e\n\u003cp\u003e27.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Kaur, I. et al. Analysis of CFH, TLR4, and APOE polymorphism in India suggests the Tyr402His variant of CFH to be a global marker for age-related macular degeneration. Invest Ophthalmol Vis Sci 47, 3729\u0026ndash;35 (2006).\u003c/p\u003e\n\u003cp\u003e28.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Kota, L. N. et al. Dementia and Diabetes Mellitus: Association with Apolipoprotein E4 Polymorphism from a Hospital in Southern India. Int J Alzheimers Dis 2012, 1\u0026ndash;4 (2012).\u003c/p\u003e\n\u003cp\u003e29.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Kumar, P. et al. Apolipoprotein E gene polymorphisms in patients with premature myocardial infarction: a case-controlled study in Asian Indians in North India. Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 40, 382\u0026ndash;387 (2003).\u003c/p\u003e\n\u003cp\u003e30.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sureshkumar, R. et al. ApoE4 and late onset depression in Indian population. J Affect Disord 136, 244\u0026ndash;248 (2012).\u003c/p\u003e\n\u003cp\u003e31.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Luthra, K. et al. Apolipoprotein E Gene Polymorphism in Indian Patients with Alzheimer\u0026rsquo;s Disease and Vascular Dementia. Dement Geriatr Cogn Disord 17, 132\u0026ndash;135 (2004).\u003c/p\u003e\n\u003cp\u003e32.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Mansoori, N. et al. IL-6\u0026ndash;174 G/C and ApoE Gene Polymorphisms in Alzheimer\u0026rsquo;s and Vascular Dementia Patients Attending the Cognitive Disorder Clinic of the All India Institute of Medical Sciences, New Delhi. Dement Geriatr Cogn Disord 30, 461\u0026ndash;468 (2010).\u003c/p\u003e\n\u003cp\u003e33.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Meena, K. et al. Cholesterol ester transfer protein and apolipoprotein E gene polymorphisms in hyperlipidemic Asian Indians in North India. Mol Cell Biochem 352, 189\u0026ndash;196 (2011).\u003c/p\u003e\n\u003cp\u003e34.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Misra, A., Chakrabarti, S. S., Gambhir, I. S., Kaur, U. \u0026amp; Prasad, S. APOE4 allele in north Indian elderly patients with dementia or late onset depression-a multiple-disease case control study. Mol Biol Res Commun 8, 135\u0026ndash;140 (2019).\u003c/p\u003e\n\u003cp\u003e35.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Murry, B., Vakha, N., Achoubi, N., Sachdeva, M. P. \u0026amp; Saraswathy, K. N. APOE, MTHFR, LDLR and ACE polymorphisms among Angami and Lotha Naga populations of Nagaland, India. J Community Health 36, 975\u0026ndash;985 (2011).\u003c/p\u003e\n\u003cp\u003e36.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Pal, P. et al. Role of Apolipoprotein E, Cathepsin D, and Brain-Derived Neurotrophic Factor in Parkinson\u0026rsquo;s Disease: A Study from Eastern India. Neuromolecular Med 21, 287\u0026ndash;294 (2019).\u003c/p\u003e\n\u003cp\u003e37.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Pandey, P., Pradhan, S. \u0026amp; Mittal, B. Presenilin Gene Predisposes to Late-Onset Degenerative but Not Vascular Dementia: A Comparative Study of PS1 and ApoE Genes in a North Indian Cohort. Dement Geriatr Cogn Disord 24, 151\u0026ndash;161 (2007).\u003c/p\u003e\n\u003cp\u003e38.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Periyasamy, S. et al. Association Studies of Specific Cholesterol Related Genes (APOE, LPL, and CETP) with Lipid Profile and Memory Function: A Correlative Study Among Rural and Tribal Population of Dharmapuri District, India. Journal of Alzheimer\u0026rsquo;s Disease 60, S195\u0026ndash;S207 (2017).\u003c/p\u003e\n\u003cp\u003e39.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Rahman, N. et al. Association of APOE (rs429358 and rs7412) and PON1 (Q192R and L55M) Variants with Myocardial Infarction in the Pashtun Ethnic Population of Khyber Pakhtunkhwa, Pakistan. Genes (Basel) 14, 687 (2023).\u003c/p\u003e\n\u003cp\u003e40.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Ranjith, N., Pegoraro, R. J. \u0026amp; Rom, L. Lipid profiles and associated gene polymorphisms in young asian indian patients with acute myocardial infarction and the metabolic syndrome. Metab Syndr Relat Disord 7, 571\u0026ndash;578 (2009).\u003c/p\u003e\n\u003cp\u003e41.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Rastogi, P. et al. Thrombophilic risk factors are laterally associated with Apolipoprotein E gene polymorphisms in deep vein thrombosis patients: An Indian study. Phlebology 34, 324\u0026ndash;335 (2019).\u003c/p\u003e\n\u003cp\u003e42.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Roy, S. et al. Influence of Apolipoprotein E polymorphism on susceptibility of Wilson disease. Ann Hum Genet 82, 53\u0026ndash;59 (2018).\u003c/p\u003e\n\u003cp\u003e43.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Sapkota, B. et al. Association of APOE polymorphisms with diabetes and cardiometabolic risk factors and the role of APOE genotypes in response to anti-diabetic therapy: results from the AIDHS/SDS on a South Asian population. J Diabetes Complications 29, 1191\u0026ndash;1197 (2015).\u003c/p\u003e\n\u003cp\u003e44.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Seet, W. T., Mary Anne, T. J. A. \u0026amp; Yen, T. S. Apolipoprotein E genotyping in the Malay, Chinese and Indian ethnic groups in Malaysia\u0026mdash;a study on the distribution of the different apoE alleles and genotypes. Clinica Chimica Acta 340, 201\u0026ndash;205 (2004).\u003c/p\u003e\n\u003cp\u003e45.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Asita De Silva, H. Alzheimer\u0026rsquo;s Disease in Sri Lanka. Journal of the Ceylon College of Physicians vol. 36 (2003).\u003c/p\u003e\n\u003cp\u003e46.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Singh, P., Singh, M., Gerdes, U. \u0026amp; Mastana, S. S. Apolipoprotein E polymorphism in India: high APOE*E3 allele frequency in Ramgarhia of Punjab. Anthropol Anz 59, 27\u0026ndash;34 (2001).\u003c/p\u003e\n\u003cp\u003e47.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Singh, P. P., Singh, M. \u0026amp; Mastana, S. S. APOE distribution in world populations with new data from India and the UK. Ann Hum Biol 33, 279\u0026ndash;308 (2006).\u003c/p\u003e\n\u003cp\u003e48.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Singh, P. P., Naz, I., Gilmour, A., Singh, M. \u0026amp; Mastana, S. Association of APOE (Hha1) and ACE (I/D) gene polymorphisms with type 2 diabetes mellitus in North West India. Diabetes Res Clin Pract 74, 95\u0026ndash;102 (2006).\u003c/p\u003e\n\u003cp\u003e49.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Srivastava, A., Mittal, B., Prakash, J., Srivastava, P. \u0026amp; Srivastava, N. Analysis of MC4R rs17782313, POMC rs1042571, APOE-Hha1 and AGRP rs3412352 genetic variants with susceptibility to obesity risk in North Indians. Ann Hum Biol 43, 285\u0026ndash;288 (2016).\u003c/p\u003e\n\u003cp\u003e50.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Tanguturi, P., Pullareddy, B., Sampath Kumar, P. \u0026amp; Murthy, D. K. Association between apolipoprotein e gene polymorphism and myocardial infarction. Biochem Genet 51, 398\u0026ndash;405 (2013).\u003c/p\u003e\n\u003cp\u003e51.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Thelma, B. K. et al. APOE Polymorphism in a Rural Older Population-Based Sample in India. Hum Biol 73, 135\u0026ndash;144 (2001).\u003c/p\u003e\n\u003cp\u003e52.\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Cheong, H. S. et al. Spontaneous bacterial peritonitis caused by Streptococcus pneumoniae in patients with liver cirrhosis. Journal of Infection vol. 59 218\u0026ndash;219 Preprint at https://doi.org/10.1016/j.jinf.2009.07.006 (2009).\u003c/p\u003e\n\u003cp\u003e53. \u0026nbsp; \u0026nbsp; \u0026nbsp;Yousuf, A. et al. Genetic Variation of ApoE Gene in Ethnic Kashmiri Population and Its Association with Outcome After Traumatic Brain Injury. Journal of Molecular Neuroscience 56, 597\u0026ndash;601 (2015).\u003c/p\u003e\n\u003cp\u003eTable 2 Pooled proportion of genotype and allele frequency in general population\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePooled proportion in % (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 250px;\"\u003e\n \u003cp\u003eHeterogeneity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ep value Publication Bias\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;2/\u0026epsilon;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.35 (0.2, 0.5)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e15.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;2/\u0026epsilon;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e7.5 (6.6, 8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e72.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;2/\u0026epsilon;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.785 (0.6, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e54.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;3/\u0026epsilon;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e73.7 (71.3, 76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e90.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;3/\u0026epsilon;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e14 (12.1, 15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e91.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;4/\u0026epsilon;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.764 (0.6, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e33.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAllele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePooled Frequency (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 250px;\"\u003e\n \u003cp\u003eHeterogeneity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eP value Publication Bias\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.0529 (0.045, 0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e89.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.851 (0.838, 0.865)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e92.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e0.0885 (0.079, 0.098)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e88.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5554316/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5554316/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis systematic review and meta-analysis assesses the distribution and health implications of apolipoprotein E (ApoE) ε2, ε3, and ε4 alleles, which play crucial roles in lipoprotein metabolism, in South Asian populations, with a focus on neurodegenerative diseases, movement disorders, mental health disorders, cardiovascular disorders, metabolic disorders and trauma-related disorders. A total of 53 studies identified through comprehensive searches in PubMed, Embase, and Google Scholar up to July 31, 2024, were included on the basis of predefined eligibility criteria after Risk Of Bias Assessment via the New York Ottawa Scale. ε3/ε3 was found to be the most prevalent genotype, followed by ε3/ε4 and ε2/ε3. ε4-containing genotypes were found to be strongly associated with susceptibility to Alzheimer's disease, coronary artery disease, vascular dementia, and obesity, whereas the ε2/ε3 and ε2 alleles showed protective effects in some conditions. These studies had several limitations, including data gaps for specific health conditions, underrepresentation of some South Asian countries, and heterogeneity in outcomes. Despite gaps in the data from a number of countries and for specific health conditions under study, this review reflects South Asian specificity of ApoE polymorphism‒disease associations, highlighting the need for targeted genetic research and tailored public health strategies to advance personalized medicine and healthcare policies in this region. There was no specific funding for this study. The study was registered in PROSPERO (registration number CRD42024575197).\u003c/p\u003e","manuscriptTitle":"ApoE Polymorphism Analysis in Health and Disease of South Asian Populations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-02 06:49:48","doi":"10.21203/rs.3.rs-5554316/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a2b84dcb-768c-4527-a212-e5b760566139","owner":[],"postedDate":"July 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50680749,"name":"Biological sciences/Biochemistry"},{"id":50680750,"name":"Biological sciences/Genetics"}],"tags":[],"updatedAt":"2025-07-02T06:49:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-02 06:49:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5554316","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5554316","identity":"rs-5554316","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}