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We identified 17,349 articles based on the literature searches, 11,391 non-duplicated articles were included in the title and abstract screening. Articles were excluded for non-human subjects (n = 3,225), irrelevant themes (n = 2,904), gene expression studies (n = 1,759), review articles (n = 1,325), duplicates (n = 846), or conference abstracts (n = 548), and the remaining 784 articles were included in the full-text review (Figure 1). In total, 399 eligible studies were identified, including 16 GWASs, 2 WES studies, and 381 candidate gene association studies. Of these, 205 studies with sufficient data were included in the meta-analysis of 25 variants of 17 genes.
Among the 16 GWASs, eight were conducted in the United States, four in Japan, two in South Korea, one in Australia, and one in Italy. Thirteen GWASs were conducted in adults, 2 studies were conducted in children, and 1 each in adults and children. The mean sample size was 5,710 ± 7,595 (ranged 234–27,374). At the same time, subsequent validation studies were performed followed by five GWAS studies. The basic characteristics of the GWASs are shown in Supplementary Table S1 (available in www.besjournal.com).
The characteristics of the 381 candidate gene association studies are presented in Supplementary Table S2 (available in www.besjournal.com). These studies analyzed 465 genetic variants in 173 candidate genes. The first candidate gene association study for NAFLD was published in 1998 and the number of such studies has gradually increased in recent decades. Most studies were conducted in China (n = 194), followed by Italy (n = 37), Japan (n = 21), Turkey (n = 18), Iran (n = 17), India (n = 16), the United States (n = 13), Egypt (n = 8), and other countries (n = 57). The ethnic distribution was dominated by Asian (n = 251) and Caucasian (n = 102) populations. The vast majority of the studies included adults (n = 349), and the remaining 32 studies were conducted in children or a mixed population. The mean NOS score was 6.36 ± 1.11, suggesting that the overall research quality was acceptable.
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In total, 72 variants were found to be significantly associated with NAFLD risk in the GWASs (Supplementary Table S1). Specifically, 52 variants were identified in adults, 15 variants were reported in children, and 6 variants were reported in both adults and children. Notably, PNPLA3 rs738409 has been reported not only in adults, but also in mixed adults and children. In addition, two WES studies have shown that three variants of two genes (PNPLA3 and PMPT) are associated with NAFLD susceptibility in adults.
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Among the 465 genetic variants, common variants (416 variants in 157 genes) (MAF ≥ 5%) included synonymous single nucleotide polymorphisms (SNPs; n = 20), non-coding transcript SNPs (n = 8), intronic SNPs (n = 208), SNPs in 5´ or 3´ untranslated regions (UTRs; n = 28), missense variants (n = 66), upstream variants (n = 46), downstream variants (n = 4) and others (n = 36). Rare variants (49 variants in 34 genes) (MAF < 5%) included synonymous variants (n = 1), non-coding transcript variants (n = 2), intronic variants (n = 17), variants in 5´ or 3´ UTRs (n = 6), missense variants (n = 21), and two upstream variants (Supplementary Table S3, available in www.besjournal.com). Based on the main function of each gene, the 173 genes were divided into eight categories: lipid synthesis and metabolism (n = 49), insulin resistance and glucose metabolism (n = 10), adipokines/adipokine receptors (n = 6), energy metabolism and obesity (n = 6), oxidative stress and antioxidants (n = 22), inflammatory and immune response (n = 32), liver fibrosis (n = 11) and others (n = 37), as shown in Supplementary Table S4 (available in www.besjournal.com).
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As shown in Table 1, 25 variants of the 17 genes were included in the meta-analysis. The information extracted for each variant used in the meta-analysis is presented in Supplementary Table S5 (available in www.besjournal.com). These meta-analyses included a mean of 14 studies (range: 6–75) and 3281 participants (range: 1,784–42,903). 11 variants in 10 genes showed statistically significant associations with NAFLD (P < 0.05), including four genes related to lipid synthesis and metabolism (MBOAT7, PEMT, PNPLA3, TM6SF2), 1 gene related to insulin resistance and glucose metabolism (GCKR), 2 genes related to adipokines/adipokine receptors (ADIPOQ, LEPR), 2 genes related to oxidative stress and antioxidants (HFE, MTHFR), and 1 gene related to inflammatory and immune response (TNF). Moreover, all 11 variants in 10 genes showed positive associations with NAFLD, and the highest risk factor for NAFLD was PNPLA3 rs738409 (OR: 1.841, 95% CI: 1.691–2.004). The cumulative epidemiological evidence of a significant association was graded as strong for two variants in two genes (HFE, TNF), moderate for four variants in three genes (TM6SF2, GCKR, and ADIPOQ), and weak for five variants in five genes (MBOAT7, PEMT, PNPLA3, LEPR, and MTHFR), based on the Venice criteria.
Gene and function Variant Alleles MAF Number assessed Allelic contrasts Heterogeneity Venice criteria gradec Cumulative evidence of associationd Studies Cases Controls OR (95% CI)a P value P valueb I2 Lipid synthesis and metabolism related genes APOC3 rs2854116 T vs. C 0.55 (T) 11 3,792 4,601 0.99 (0.89−1.10) 0.826 0.004 63 ACC + rs2854117 C vs. T 0.67 (C) 9 3,538 3,819 1.02 (0.95−1.10) 0.577 0.370 8 AAC + LYPLAL1* rs12137855 T vs. C 0.20 (T) 13 4,369 5,292 0.98 (0.89−1.09) 0.753 0.326 12 AAC + MBOAT7 rs641738 C vs. T 0.57 (C) 12 4,351 10,830 1.07 (1.00−1.14) 0.048 0.528 0 AAC + MTTP rs1800591 T vs. G 0.15 (T) 11 1,483 1,490 0.89 (0.59−1.36) 0.592 < 0.001 88 ACC + PEMT rs7946 T vs. C 0.70 (T) 10 1,090 1,390 1.51 (1.11−2.06) 0.008 < 0.001 73 ACA + PNPLA3 rs738409 G vs. C 0.26 (G) 75 18,193 24,710 1.84 (1.69−2.00) < 0.001 < 0.001 85 ACA + PPARG rs1801282 G vs. C 0.11 (G) 9 2.108 2.740 0.88 (0.70−1.10) 0.260 0.084 43 ABC + PPARGC1A* rs8192678 T vs. C 0.33 (T) 6 726 1,058 1.05 (0.78−1.41) 0.735 0.011 66 ACC + TM6SF2 rs58542926 T vs. C 0.07 (T) 24 5,499 12,677 1.69 (1.47−1.93) < 0.001 0.068 33 ABA ++ Insulin resistance and glucose metabolism related genes GCKR rs780094 T vs. C 0.40 (T) 23 6,401 9,983 1.18 (1.12−1.26) < 0.001 0.030 39 ABA ++ rs1260326 T vs. C 0.40 (T) 9 1,655 2,527 1.48 (1.67−1.87) 0.001 < 0.001 46 ABA ++ PPP1R3B* rs4240624 G vs. A 0.11 (G) 7 2,362 3,292 0.88 (0.68−1.14) 0.339 0.367 8 AAC + Adipokines/adipokine receptors related genes ADIPOQ rs1501299 T vs. G 0.27 (T) 13 2,261 2,190 0.97 (0.74−1.29) 0.849 < 0.001 88 ACC + rs266729 G vs. C 0.23 (G) 8 1,875 1,466 1.61 (1.36−1.91) < 0.001 0.142 40 ABA ++ rs2241766 G vs. T 0.10 (G) 13 2,187 2,072 1.09 (0.92−1.28) 0.335 0.012 54 ACC + LEPR rs1137100 G vs. A 0.27 (G) 7 1,382 1,304 1.02 (0.83−1.26) 0.863 0.131 39 ABC + rs1137101 G vs. A 0.46 (A) 6 1,591 1,535 1.82 (1.41−2.54) < 0.001 0.019 63 ACA + Oxidative stress and antioxidants related genes HFE rs1800562 A vs. G 0.05 (A) 15 2,261 5,508 1.83 (0.99−3.40) 0.056 < 0.001 63 ACA + rs1799945 G vs. C 0.14 (G) 14 1,993 2,475 1.24 (1.04−1.48) 0.019 0.192 24 AAA +++ MTHFR rs1801131 C vs. A 0.30 (C) 7 2,122 1,157 1.24 (0.93−1.65) 0.141 < 0.001 76 ACA + rs1801133 T vs. C 0.34 (T) 9 2,303 1,399 1.30 (1.06−1.59) 0.012 0.006 63 ACA + Inflammatory and immune response related genes TNF rs3615525 A vs. G 0.05 (A) 14 2,055 1,594 1.82 (1.42−2.34) < 0.001 0.219 23 AAA +++ rs1800629 A vs. G 0.15 (A) 13 2,176 1,789 1.29 (0.99−1.69) 0.064 0.115 34 ABA ++ Other functional genes NCAN* rs2228603 T vs. C 0.07 (T) 11 4,251 6,105 0.97 (0.86−1.08) 0.544 0.712 0 AAC + Note. OR: odds ratio; CI: confidence interval; G: guanine; A, adenine; C: cytosine; T: thymine; MAF: minor-allele frequency. *Genes and loci that have not been meta-analyzed in published literature; aSummary ORs are based on random-effects allelic contrasts comparing minor and major alleles (based on frequencies in the control samples); bBased on the Q statistic across crude ORs calculated for each study; cDegree of ‘epidemiological credibility’ based on the interim Venice guidelines (A, strong; B, modest; C, weak); dCumulative epidemiological evidence as graded by Venice criteria as strong (+++), moderate (++), or weak (+) for association with NAFLD risk. Table 1. Results of random effects meta-analyses using allelic contrasts for polymorphisms
Of the 25 variants in meta-analyses, seven variants had little or no inter-study heterogeneity (I2 < 25%), 7 variants showed moderate heterogeneity (25% ≤ I2 ≤ 50%), and 11 variants showed high inter-study heterogeneity (I2 > 50%). The results of the dominant, recessive, heterozygous, and homozygous genetic models are shown in Supplementary Table S6 (available in www.besjournal.com). The allele contrast model identified more significant associations than the other models did.
All meta-analyses included a population of mixed ethnicities, except for LEPR rs1137100 and LEPR rs1137101, for which data were available only among Asian adults. Stratified meta-analyses according to ethnicity were conducted for the five variants of the four genes (Table 2). We found that PNPLA3 rs738409 was associated with NAFLD in all ethnicities, but showed the highest OR value (OR: 2.45, 95% CI: 2.04–2.95) in Caucasians and the lowest OR value (OR: 1.66, 95% CI: 1.51–1.83) in Asians. The three variants showed significant associations in only one ethnic population in the stratified analysis. Despite significant associations with NAFLD in the total population, significant associations were observed for GCKR rs780094 in Asians, GCKR rs1260326 in Caucasians, and MTHFR rs1801133 in Asians.
Gene and function Variant Alleles Subgroup Number assessed Allelic contrasts Heterogeneity Venice criteria gradec Cumulative evidence of associationd Studies Cases Controls OR (95% CI)a P value P valueb I2 Lipid synthesis and metabolism related genes MBOAT7 rs641738 C vs. T Total 12 4,351 10,830 1.07 (1.00−1.14) 0.048 0.528 0 AAC + Caucasians 7 2,464 2,166 1.07 (0.98−1.16) 0.144 0.448 0 AAC + Asians 5 1,887 8,664 1.07 (0.97−1.19) 0.188 0.374 6 AAC + PNPLA3 rs738409 G vs. C Total 75 18,193 24,710 1.84 (1.69−2.00) < 0.001 < 0.001 85 ACA + Caucasians 21 4,144 3,327 2.45 (2.04−2.95) < 0.001 < 0.001 77 ACA + Asians 45 12,792 20,320 1.66 (1.51−1.83) < 0.001 < 0.001 86 ACA + Others 4 742 299 1.89 (1.52−2.37) < 0.001 0.961 0 AAA +++ Insulin resistance and glucose metabolism related genes GCKR rs780094 T vs. C Total 23 6,401 9,983 1.18 (1.12−1.26) < 0.001 0.030 39 ABA ++ Asians 21 5,603 9,456 1.17 (1.10−1.26) < 0.001 0.040 38 ABA ++ Caucasians 2 798 527 1.34 (0.91−1.98) 0.142 0.065 71 ABC + rs1260326 T vs. C Total 9 1,655 2,527 1.48 (1.67−1.87) 0.001 < 0.001 46 ABA +++ Asians 4 1,023 992 1.61 (0.99−2.62) 0.057 < 0.001 93 ACA + Caucasians 3 393 552 1.42 (1.17−1.71) < 0.001 0.776 0 BAA ++ Others 2 239 983 1.33 (0.74−2.36) 0.338 0.038 77 ACA + Oxidative stress and antioxidants related genes MTHFR rs1801133 T vs. C Total 9 2,303 1,399 1.30 (1.06−1.59) 0.012 0.006 63 ACA + Caucasians 4 1,663 714 1.20 (0.85−1.68) 0.296 0.013 72 ACA + Asians 3 471 506 1.51 (1.07−2.12) 0.019 0.077 61 BCA + Hispanics 2 169 179 1.28 (0.63−2.58) 0.499 0.058 72 BCA + Note. OR: odds ratio; G: guanine; C: cytosine; T: thymine. aSummary ORs are based on random-effects allelic contrasts comparing minor and major alleles (based on frequencies in the control samples); bBased on the Q statistic across crude ORs calculated for each study; cDegree of ‘epidemiological credibility’ based on the interim Venice guidelines (A, strong; B, modest; C, weak); dCumulative epidemiological evidence as graded by Venice criteria as strong (+++), moderate (++), or weak (+) for association with NAFLD risk. Table 2. Results of random effects meta-analyses of alleles using allelic contrasts for polymorphisms stratified by ethnicity
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By 30 September, 2022, a total of 75 meta-analyses on NAFLD genetic associations were published involving 21 variants of 13 genes. The results of meta-analyses that were published most recently or included the largest number of studies were extracted for each variant (Table 3). Compared with previously published meta-analyses, meta-analyses for four variants in four genes were conducted for the first time in this study, and all four variants showed no association with NAFLD risk (LYPLAL1 rs12137855, PPARGC1A rs8192678, PPP1R3B rs4240624, NCAN rs2228603). Among the variants that have been meta-analyzed in the past, consistent results were observed for 15 variants in 11 genes, where 10 variants in 9 genes were associated with increased risk of NAFLD (TNF rs3615525, ADIPOQ rs266729, GCKR rs780094, GCKR rs1260326, PNPLA3 rs738409, MTHFR rs1801133, TM6SF2 rs58542926, PEMT rs7946, LEPR rs1137101, HFE rs1799945) and 5 variants in 4 genes (TNF rs1800629, PPARG rs1801282, APOC3 rs2854116, APOC3 rs2854117, LEPR rs1137100) showed no associations with NAFLD. Five variants in four genes (ADIPOQ rs1501299, ADIPOQ rs2241766, MTTP rs1800591, MTHFR rs1801131, HFE rs1800562) showed significant associations in previous meta-analyses but showed insignificant associations in this study. In contrast, MBOAT7 rs641738 was not associated with NAFLD in previous meta-analyses but was significantly associated with NAFLD in this study.
Gene Study Polymorphism Prior meta sample size: cases; controls (number of samples) Model Published meta
OR (95% CI)Published Het. Meta Our new meta sample size: cases; controls (number of samples) Model New meta
OR (95% CI)Het. Meta TNF Wang et al. 2011 rs3615525 771; 787 (7) GA/AA vs. GG 2.06 (1.58−2.69)a 0.160 2,055; 1,594 (14) A vs. G 1.82 (1.42−2.34) 0.219 rs1800629 837; 990 (8) GA/AA vs. GG 1.08 (0.82−1.42)a 0.860 2,176; 1,789 (13) A vs. G 1.29 (0.99−1.69) 0.115 PPARG Zhang et al. 2015 rs1801282 1,697; 2,427 (8) GC/GG vs. CC 0.93 (0.63−1.38) < 0.001 2,108; 2,740 (9) G vs. C 0.88 (0.70−1.10) 0.084 ADIPOQ Wang et al. 2014 rs266729 876; 989 (7) GG/GC vs. CC 1.52 (1.10−2.09)a 0.280 1,875; 1,466 (8) G vs. C 1.61 (1.36−1.91) 0.142 Wang et al. 2016 rs1501299 1,117; 1,555 (10) G vs. T 1.27 (1.10−1.48)a 0.533 2,261; 2,190 (13) T vs. G 0.97 (0.74−1.29) < 0.001 rs2241766 1,117; 1,555 (10) T vs. G 1.33 (1.12−1.58)a 0.151 2,187; 2,072 (13) G vs. T 1.09 (0.92−1.28) 0.012 APOC3 Li et al. 2017 rs2854116 2,111; 1,866 (9) C vs. T 1.39 (0.96−2.02)a 0.001 3,792; 4,601 (11) T vs. C 0.99 (0.89−1.10) 0.004 rs2854117 2,111; 1,866 (9) T vs. C 1.05 (0.92−1.19)a 0.840 3,538; 3,819 (9) C vs. T 1.02 (0.95−1.10) 0.370 GCKR Li et al. 2021 rs780094 5,115; 11,812 (20) T vs. C 1.20 (1.11−1.29) 0.020 6,401; 9,983 (23) T vs. C 1.17 (1.10−1.24) < 0.001 rs1260326 2,238; 8,995 (9) T vs. C 1.32 (1.22−1.42) 0.560 1,655; 2,527 (9) T vs. C 1.27 (1.14−1.42) < 0.001 MTHFR Sun et al. 2016 rs1801131 364; 611 (5) C vs. A 1.53 (1.13−2.07) 0.001 2,122; 1,157 (7) C vs. A 1.24 (0.93−1.65) < 0.001 rs1801133 737; 1,160 (8) TT vs. TC/CC 1.42 (1.07−1.88) 0.160 2,303; 1,399 (9) T vs. C 1.30 (1.06−1.59) 0.006 MBOAT7 Xia et al. 2019 rs641738 2,560; 8,738 (5) C vs. T 0.99 (0.93−1.05)a - 4,351; 10,830 (12) C vs. T 1.07 (1.00−1.14) 0.528 TM6SF2 Chen et al. 2019 rs58542926 3,075; 3,000 (13) Unknown 0.55 (0.48−0.63) - 5,499; 12,677 (24) T vs. C 1.69 (1.47−1.93) 0.068 PEMT Tan et al. 2016 rs7946 792; 2,722 (6) TT/TC vs. CC 1.62 (1.10−0.39) - 1,090; 1,390 (10) T vs. C 1.51 (1.11−2.06) < 0.001 LEPR Pan et al. 2018 rs1137100 1,111; 1,132 (6) A vs. G 1.01 (0.87−1.18) 0.110 1,382; 1,304 (7) G vs. A 1.02 (0.83−1.26) 0.131 rs1137101 1,298; 1,348 (5) A vs. G 0.57 (0.50−0.65) 0.140 1,591; 1,535 (6) G vs. A 1.82 (1.41−2.54) 0.019 HFE Ye et al. 2016 rs1800562 1,846; 7,037 (11) A vs. G 1.95 (1.16−3.28) < 0.001 2,261; 5,508 (15) A vs. G 1.83 (0.99−3.40) < 0.001 rs1799945 3,945; 12,332 (16) G vs. C 1.21 (1.07−1.38)a 0.338 1,993; 2,475 (14) G vs. C 1.24 (1.04−1.48) 0.192 Note. aFixed effects model was used in prior meta-analysis-: P-value is not reported. Table 3. Previously published meta-analyses results compared to meta-analyses in this study
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Literature Searches and Study Characteristics
Summary of GWASs and WES Study
Summary of Candidate Gene Association Studies
Meta-Analysis of Associations between Genetic Variations and NAFLD
Comparison between Previously Published Meta-Analysis Results and this Meta-Analysis
23334+Supplementary Materials.pdf |