Angiotensin-converting enzyme polymorphisms AND Alzheimer’s disease susceptibility: An updated meta-analysis

Xiao-Yu Xin; Ze-Hua Lai; Kai-Qi Ding; Li-Li Zeng; Jian-Fang Ma

doi:10.1371/journal.pone.0260498

. 2021 Nov 24;16(11):e0260498. doi: 10.1371/journal.pone.0260498

Angiotensin-converting enzyme polymorphisms AND Alzheimer’s disease susceptibility: An updated meta-analysis

Xiao-Yu Xin ¹, Ze-Hua Lai ¹, Kai-Qi Ding ¹, Li-Li Zeng ^1,^*, Jian-Fang Ma ^1,^*

Editor: Zhicheng Lin²

PMCID: PMC8612529 PMID: 34818351

Abstract

Background

Many studies among different ethnic populations suggested that angiotensin converting enzyme (ACE) gene polymorphisms were associated with susceptibility to Alzheimer’s disease (AD). However, the results remained inconclusive. In the present meta-analysis, we aimed to clarify the effect of ACE polymorphisms on AD risk using all available relevant data.

Methods

Systemic literature searches were performed using PubMed, Embase, Alzgene and China National Knowledge Infrastructure (CNKI). Relevant data were abstracted according to predefined criteria.

Results

Totally, 82 independent cohorts from 65 studies were included, focusing on five candidate polymorphisms. For rs1799752 polymorphism, in overall analyses, the insertion (I) allele conferred increased risk to AD compared to the deletion (D) allele (I vs. D: OR = 1.091, 95% CI = 1.007–1.181, p = 0.032); while the I carriers showed increased AD susceptibility compared with the D homozygotes (II + ID vs. DD: OR = 1.131, 95% CI = 1.008–1.270, p = 0.036). However, none of the positive results passed FDR adjustment. In subgroup analysis restricted to late-onset individuals, the associations between rs1799752 polymorphism and AD risk were identified using allelic comparison (OR = 1.154, 95% CI = 1.028–1.295, p = 0.015, FDR = 0.020), homozygotes comparison, dominant model and recessive model (II vs. ID + DD: OR = 1.272, 95% CI = 1.120–1.444, p < 0.001, FDR < 0.001). Nevertheless, no significant association could be revealed after excluding studies not in accordance with Hardy-Weinberg equilibrium (HWE). In North Europeans, but not in East Asians, the I allele demonstrated increased AD susceptibility compared to the D allele (OR = 1.096, 95% CI = 1.021–1.178, p = 0.012, FDR = 0.039). After excluding HWE-deviated cohorts, significant associations were also revealed under homozygotes comparison, additive model (ID vs. DD: OR = 1.266, 95% CI = 1.045–1.534, p = 0.016, FDR = 0.024) and dominant model (II + ID vs. DD: OR = 1.197, 95% CI = 1.062–1.350, p = 0.003, FDR = 0.018) in North Europeans. With regard to rs1800764 polymorphism, significant associations were identified particularly in subgroup of European descent under allelic comparison (T vs. C: OR = 1.063, 95% CI = 1.008–1.120, p = 0.023, FDR = 0.046), additive model and dominant model (TT + TC vs. CC: OR = 1.116, 95% CI = 1.018–1.222, p = 0.019, FDR = 0.046). But after excluding studies not satisfying HWE, all these associations disappeared. No significant associations were detected for rs4343, rs4291 and rs4309 polymorphisms in any genetic model.

Conclusions

Our results suggested the significant but modest associations between rs1799752 polymorphism and risk to AD in North Europeans. While rs4343, rs4291 and rs4309 polymorphisms are unlikely to be major factors in AD development in our research.

Introduction

Alzheimer’s disease (AD) is an insidious neurodegenerative disorder characterized by progressive cognitive decline, especially irreversible memory impairment. As the most common form of dementia worldwide, AD accounts for about 50~70% of all dementia cases. In China, it was estimated that 9,83 million people aged 60 years or older suffer from AD [1]. Although the precise mechanisms of pathogenesis have not yet been fully defined, with epidemiological and molecular evidence, AD is considered as a multifactorial disease attributed to a complex interaction of both genetic and environment factors. While heritable factors account for 60–80% of AD risk [2].

Despite a number of rare mutations on the Aβ precursor protein (APP), Presenilin-1 (PS1) and Presenilin-2 (PS2) relating to familial AD, which account for less than 2% of all AD cases, the apolipoprotein E (APOE) ε4 allele remains the strongest genetic risk factor for sporadic AD. Previous studies linked APOE with Aβ aggregation and clearance, tau neurofibrillary degeneration, microglia and astrocyte responses, and blood-brain barrier (BBB) disruption [3]. Presence of APOE ε4 allele increases risk of AD with a dose-dependent manner, and might lead to an earlier age of disease onset. The frequency of APOE ε4 in AD patients varied among different ethnic groups, ranging from around 40% to 60%, compared to 20%~25% in controls. Therefore, the presence of ε4 is neither necessary nor sufficient to cause the disease, indicating the participant of other heritable risk factors underlying the development of AD [4, 5].

Recently, many evidences supported that ACE participated in the pathogenesis of AD. As a membrane-bound zinc metalloprotease, ACE played an important role in Aβ degradation. Angiotensin converting enzyme (ACE) is an important component of the renin-angiotensin system (RAS), which mainly acts on promoting the formation of Angiotensin II (Ang II) from Angiotensin I (Ang I) [6]. In an 8-year longitudinal study, the mean intelligence quotient of male hypertensive patients taking ACE inhibitors declined more rapidly than that of others taking no ACE inhibitors. In human APP/ACE +/- mice, a decrease in ACE levels promoted Aβ₄₂ deposition and increased the number of apoptotic neurons [7]. Peripherally derived ACE-enhanced macrophage reduced cerebral soluble Aβ₄₂ level and alleviated vascular and parenchymal Aβ deposits [8]. All these results confirmed the role of ACE in AD development.

The ACE gene is located on chromosome 17q23. The most common polymorphism of ACE gene is the insertion/deletion (I/D) variant of 287-bp in intron 16 (rs1799752). The I/D genotype is regarded as a determinant of ACE expression levels in plasma, cells and tissues. Approximately 50% variability in plasma levels of ACE depends on the rs1799752 polymorphism [9, 10]. Individuals carrying the D allele have higher plasma ACE levels compared to I homozygotes [11]. Moreover, rs1799752 I/D polymorphism has been reported to link with coronary heart disease and cognitive impairment, for example, AD and vascular dementia (VD). Besides rs1799752 I/D polymorphism, several other polymorphisms of the ACE gene were also investigated in AD cohorts of different ethnics, such as rs1800764 T/C, rs4343 A/G, rs4291 A/T polymorphisms, et al. rs1800764 and rs4291 located in the regulatory region of ACE gene, while rs4343 in the exotic region. Though some studies have demonstrated the associations, inconsistency was still presented among different study populations. These discrepancies may be related to the small sample size of individual studies, the difference in ethnic background and the different methodologies used for analysis. While meta-analysis is a well-established means to quantitatively synthesize all association data across studies to reduce heterogeneity and identify minor genetic effects, which largely addressing the issue of sample size.

Thus, in the present study, we performed an updated meta-analysis combining all available case-control studies to derive a more precise estimation of the associations between ACE gene polymorphisms and AD susceptibility. We also stratified the study cohorts, when possible, according to the age of onset and ethnic background. Since some recent evidence suggested that the presence of APOE ε4 influence the behavioural effects of ACE I/D polymorphism in AD, and the protective effects of ACE inhibitors or angiotensin receptor blockers on cognitive decline correlated with APOE ε4 carrier status, we also performed subgroup analyses according to APOE ε4 carrier status if sufficient data could be obtained [12, 13].

Materials and methods

Literature search

We performed computerized searches of PubMed, Embase, Alzgene and China National Knowledge Infrastructure (CNKI) up to January 31^st, 2021. The following keywords were used: (angiotensin-converting enzyme or ACE or DCP1) AND (Alzheimer or dementia) AND (polymorphism or variant or allele or genotype), with no language restriction. In addition, references of retrieved articles, reviews and meta-analyses were checked manually for potential studies.

Study selection

Studies included in the meta-analysis should meet the following criteria: (1) case-control design; (2) the evaluation of the relationship between the ACE polymorphisms and AD; (3) AD was diagnosed according to generally accepted criteria, such as criteria of the National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) or of the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV), et al.; (4) genotype or allele frequencies were available in both cases and controls. Studies that performed in more than 1 population were considered as separate investigations. When the articles contained duplicated data, the most recent or complete data set was selected. Since all the included studies were gene polymorphism investigations in patients and controls, which were not suitable for randomized controlled design, no randomized controlled trial (RCT) could be identified and involved in our research.

Data extraction

Data were extracted from the eligible articles by two investigators independently and agreements were achieved on all items. The following information was collected using a predefined reporting form: name of the first author, publication year, sample size, country, racial descent, diagnosis criteria of AD, genotyping method, source of controls, distribution of allele and genotypes in both AD and control groups, and Hardy-Weinberg equilibrium (HWE) in controls. The Newcastle-Ottawa Scale (NOS) was performed to assess the methodological quality of the included studies. The total NOS score ranges from 0 to 9. If the score was 6 or more, the study was assumed to be high quality [14].

Statistical analysis

The STATA Software (version 14.0, Stata Corp) was used for analytical procedures. Hardy–Weinberg equilibrium (HWE) was assessed in the controls using the exact test. For each gene polymorphism, meta-analysis was performed only if data were available from at least 4 independent studies. We did not assume a genetic model in advance. Firstly, odds ratio was produced by allelic comparison. Secondly, we compared each genotype with one other in turn. Thirdly, we compared each genotype in turn with the other two combined. All these three methods have been widely used for pooling data in genetic association studies [15].

The strength of association was determined by pooled odds ratio (OR) along with the corresponding 95% confidence interval (CI). The Dersimonian and Laird’s Q test was performed for heterogeneity evaluation. If the p value was less than 0.10, the heterogeneity was considered statistically significant. Quantification of the heterogeneity was assessed using the I² metric, which represents the percentage of the observed between study variabilities due to heterogeneity rather than due to chance. I² ranges from 0% to 100%, with higher values indicating a greater degree of heterogeneity. Where there was significant heterogeneity among studies (I²≥50%), the pooled OR was calculated by a random-effect model (Dersimonian and Laird); Otherwise, a fixed-effect model was used (Mantel-Haenszel).

Stratified analysis was performed, when feasible, by geographic location, age of onset, or APOE ε4 status. In addition, pooled odds ratios were calculated particularly in large sample size cohorts (⩾300 participants). Cumulative meta-analysis was conducted to investigate the trend and the stability of risk effects as evidence accumulated over time. To adjust for multiple comparisons, we applied the Benjamini-Hochberg (BH) method to control false discovery rate (FDR) [16]. Publication bias was examined using both the Begg-Mazumdar test and the Egger’s regression asymmetry test.

Results

Eligible studies and candidate polymorphisms

77 articles covered 35 polymorphisms were identified as potential candidates after primary electronic searches and manual screening. Among these, 9 articles were excluded for duplicated data. 2 articles were excluded since there was no sufficient number of studies for a meta-analysis (more than four separate studies were required for a meta-analysis in the present investigation) [17, 18]. For 1 instance, because exact allele or genotype counts could not be obtained despite attempts to contact the authors, it was also not involved [19]. Therefore, 65 articles with 82 samples were finally included in our study, focusing on 5 polymorphisms as following: rs1799752 I/D, rs1800764 T/C, rs4343 A/G, rs4291 A/T, rs4309 C/T (Table 1). The mean number of samples per candidate polymorphism was 24.80 ± 19.49 (Table 2). Main diagnostic criteria for AD included NINCDS-ADRDA, DSM-IV, ICD-10, CREAD. All the included studies used standard genotyping method in laboratory. Fig 1. shows the detailed screening process for the involved literature.

Table 1. General characteristics of included studies in the present meta-analysis.

Author	Year	Country	Ethnicity	Diagnostic criteria	Sample size (cases/controls)	Polymorphisms	NOS¹
Chapman [20]	1998	Israel	European descent	NINCDS-ADRDA², probable; DSM-III-R³	49/40	1799752	8
Scacchi [21]	1998	Italy	European descent	NINCDS-ADRDA, probable	80/155	1799752	7
Alveraz [22]	1999	Spain	European descent	NINCDS-ADRDA, probable	350/517	1799752	8
Hu [23]	1999	Japan	Japanese	NINCDS-ADRDA, probable	132/257	1799752	7
Kehoe (3 cohorts) [24]	1999	Ireland	European descent	NINCDS-ADRDA	542/386	1799752	7
Palumbo [25]	1999	Italy	European descent	NINCDS-ADRDA, probable, possible	140/40	1799752	8
Crawford [26]	2000	USA	Mixed	NINCDS-ADRDA, probable, possible	171/175	1799752	9
Farrer (2 cohorts) [27]	2000	USA; Canada; Italy; Russia	European descent	NINCDS-ADRDA	386/375	1799752	8
Mattila [28]	2000	Finland	European descent	NINCDS-ADRDA, probable; CREAD	80/67	1799752	8
Myllykangas [29]	2000	Finland	European descent	CERAD4, probable, definite	121/75	1799752	8
Narain [30]	2000	UK	European descent	CERAD	239/342	1799752	7
Yang [31]	2000	China	Chinese	NINCDS-ADRDA, probable; DSM-IV5	188/227	1799752	8
Isbir [32]	2001	Turkey	European descent	NINCDS-ADRDA, probable	35/29	1799752	7
Perry [33]	2001	USA	African American	NINCDS-ADRDA, probable, definite; CERAD	111/78	1799752	8
Prince [34]	2001	Sweden	European descent	NINCDS-ADRDA, probable, definite; CERAD	204/186	4343	8
Richard (2 cohorts) [35]	2001	France	European descent	NINCDS-ADRDA, probable; DSM-III-R	56/221	1799752	9
Zuiliani [36]	2001	Italy	European descent	NINCDS-ADRDA, probable	40/54	1799752	8
Buss [37]	2002	Germany; Switzerland; Italy	European descent	NINCDS-ADRDA	261/306	1799752	8
Cheng [38]	2002	China	Chinese	NINCDS-ADRDA, probable	173/285	1799752	7
Lendon [39]	2002	UK	European descent	NINCDS-ADRDA, probable; DSM-III-R;	214/99	1799752	7
Monastero [40]	2002	Italy	European descent	NINCDS-ADRDA, probable	149/149	1799752	9
Panza [41]	2002	Italy	European descent	NINCDS-ADRDA, probable	141/268	1799752	9
Wu [42]	2002	China	Chinese	DSM-IV	96/96	1799752	7
Carbonell [43]	2003	UK	European descent	NINCDS-ADRDA possible probable	80/65	1799752	7
Kehoe (4 cohorts) [44]	2003	Sweden; UK	European descent	NINCDS-ADRDA, possible, probable, definite; CERAD	846/773	1799752,4343, 4291,1800764	9
Seripa (2 cohorts) [45]	2003	Italy; USA	European descent	NINCDS-ADRDA; probable	250/203	1799752	9
Camelo [46]	2004	Colombia	European descent	NINCDS-ADRDA; probable	83/69	1799752	8
Feng [47]	2004	China	Chinese	NINCDS-ADRDA	26/68	1799752	7
Koelsch [48]	2005	Germany	European descent	DSM-IV	351/348	1799752	9
Lehmann [49]	2005	UK	European descent	NINCDS-ADRDA; DSM-IV	203/248	1799752	8
Sleegers [50]	2005	Netherlands	European descent	NINCDS-ADRDA, probable; DSM-III-R	250/6403	1799752	9
Zhang [51]	2005	China	Chinese	NINCDS-ADRDA;	192/195	1799752	8
Blomsqvist [52]	2006	UK; Sweden	European descent	NINCDS-ADRDA, probable, definite; CERAD	940/405	4309
Keikhaee [53]	2006	Iran	European descent	NINCDS-ADRDA, probable	117/125	1799752	9
Meng [54]	2006	Israel	European descent	DSM-IV	92/166	1800764,4291,4343	7
Wang [55]	2006	China	Chinese	NINCDS-ADRDA; DSM-III-R	104/128	1799752	8
Wang [56]	2006	China	Chinese	DSM-III-R, NINCDS-ADRDA, probable	151/161	1799752	7
Wehr [57]	2006	Poland	European descent	NINCDS-ADRDA	100/144	1799752	7
Liu [58]	2007	China	Chinese	NINCDS-ADRDA, probable; DSM-IV	39/50	1799752	8
Nacmias [59]	2007	Italy	European descent	DSM-IV	388/303	1799752	9
Bruandet [60]	2008	France	European descent	NINCDS-ADRDA; DSM-IV	141/6467	4291,4343	8
Han [61]	2008	China	Chinese	NINCDS-ADRDA, probable	55/59	1799752	9
Trebunova [62]	2008	Slovakia	European descent	NINCDS-ADRDA	70/126	1799752	8
Giedraitis [63]	2009	Sweden	European descent	DSM-IV, NINCDS-ADRDA	86/404	4343	9
Helbecque [64]	2009	France, UK, Spain, Netherlands, Italy	European descent	NINCDS-ADRDA; DSM-III-R	376/444	4291,4343	7
Vardy [65]	2009	UK	European descent	NINCDS-ADRDA	94/188	1799752	8
Corneveaux [66]	2010	UK, USA, Netherland	European descent	CERAD	1019/591	1800764	9
Feulner [67]	2010	Germany	European descent	NINCDS-ADRDA	491/479	4309	8
Ning [68]	2010	China	Chinese	NINCDS-ADRDA; DSM-IV	144/476	1799752,4343, 1800764	8
Sarajarvi [69]	2010	Finland	European descent	NINCDS-ADRDA, probable	642/682	4343	7
shulman [70]	2010	USA	European descent	CERAD	173/131	1800764	9
Belbin (10 cohorts) [71]	2011	UK	European descent	NINCDS-ADRDA; CERAD	3930/4282	4291,4343,1800764	7
Cousin [72]	2011	France	European descent	NINCDS-ADRDA, probable	428/475	1799752,4291	8
Ghebranious [73]	2011	USA	European descent	NINCDS-ADRDA	153/302	4343,4291,1800764	7
Lucatelli [74]	2011	Brazil	Mixed	DSM-IV, NINCDS-ADRDA	35/85	1799752	8
Nirmal [75]	2011	India	Indian	DSM-IV	95/130	1799752	7
Yang [76]	2011	China	Chinese	NINCDS-ADRDA, probable	257/137	1799752	9
Zhang [77]	2014	China	Chinese	NINCDS-ADRDA	96/102	1799752	7
Deng [78]	2015	China	Chinese	NINCDS-ADRDA	201/257	4291,4309,4343	7
Achouri-Rassa [79]	2016	Tunis	European descent	DSM-IV	85/90	1799752	9
Fekih-Mrissa [80]	2017	Tunis	European descent	DSM-IV, NINCDS-ADRDA	60/120	1799752	9
Wang [81]	2017	China	Chinese	NINCDS-ADRDA	113/142	4343,1800764	7
Li [82]	2018	China	Chinese	Chinese Medical Association Criteria	52/52	1799752	7
Durmaz [83]	2019	Turkey	European descent	DSM-IV	100/100	1799752	8
Shu [84]	2019	China	Chinese	NINCDS-ADRDA	149/113	1799752	7

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1. Newcastle-Ottawa Scale (NOS) score for each study.

2. National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer’s Disease and Related Disorders Association criteria.

3. Revised Diagnostic and Statistical Manual of Mental Disorders-III criteria.

4. Consortium to Establish a Registry for Alzheimer’s Disease criteria.

5. Diagnostic and Statistical Manual of Mental Disorders-IV criteria.

Table 2. Summary of ACE polymorphisms included in the present meta-analysis.

Polymorphisms	No. of cohorts	Total cases	Total controls
rs1799752 I/D	57	8619	15718
rs4343 A/G	23	9783	16890
rs4291 A/T	20	5973	13044
rs1800764 T/C	20	6371	6787
rs4309 C/T	4	1187	1056

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rs1799752 I/D and AD risk

Totally, 57 samples were found dealing with rs1799752 polymorphism and AD risk, comprising 8619 cases and 15718 controls. Since 1 sample just provided allele counts, it was only analyzed in the allelic comparison [74]. In overall analyses, the associations between rs1799752 polymorphism and AD susceptibility were identified under allelic comparison (I vs. D: OR = 1.091, 95% CI = 1.007–1.181, p = 0.032) and dominant model (II + ID vs. DD: OR = 1.131, 95% CI = 1.008–1.270, p = 0.036). However, the FDR values were both higher than 0.05, suggesting that the associations were not reliable. Sensitivity analysis by excluding studies not in accordance with HWE obtained similar results (Table 3). When analyses were performed particularly in investigations published in English, no reliable associations were identified either.

Table 3. Pooled odds ratios for rs1799752 polymorphism and AD susceptibility.

Comparisons	Data	No. of cohorts	Cases/controls	OR	95% CI	z	p	FDR	I² (%)	p(Q)	Effect model
I/D	overall	57	8619/15718	1.091	1.007–1.181	2.14	0.032	0.092	67.8	<0.001	random
	overall in HWE	47	7219/14105	1.075	0.984–1.174	1.60	0.109	0.194	68.5	<0.001	random
	late onset	18	2664/3322	1.154	1.028–1.295	2.42	0.015	0.020	51.4	0.006	random
	late onset in HWE	15	2133/2625	1.122	0.982–1.281	1.69	0.091	0.137	52.6	0.009	random
II/ID	overall	56	8584/15633	1.067	0.989–1.150	1.68	0.093	0.112	49.9	<0.001	fixed
	overall in HWE	47	7219/14105	1.054	0.969–1.145	1.23	0.219	0.263	45.8	<0.001	fixed
	late onset	18	2664/3322	1.214	1.060–1.390	2.80	0.005	0.010	46.5	0.016	fixed
	late onset in HWE	15	2133/2625	1.192	1.018–1.396	2.19	0.029	0.087	48.3	0.019	fixed
ID/DD	overall	56	8619/15718	1.117	0.999–1.250	1.93	0.053	0.092	52.8	<0.001	random
	overall in HWE	47	7219/14105	1.094	1.012–1.182	2.27	0.023	0.138	49.8	<0.001	fixed
	late onset	18	2664/3322	1.098	0.966–1.247	1.43	0.151	0.151	47.4	0.014	fixed
	late onset in HWE	15	2133/2625	1.098	0.953–1.264	1.29	0.196	0.200	10.9	0.331	fixed
II/DD	overall	56	8619/15718	1.154	0.994–1.341	1.88	0.061	0.092	60.3	<0.001	random
	overall in HWE	47	7219/14105	1.138	0.963–1.344	1.52	0.129	0.194	60.9	<0.001	random
	late onset	18	2664/3322	1.308	1.120–1.528	3.39	0.001	0.003	39.5	0.044	fixed
	late onset in HWE	15	2133/2625	1.218	1.021–1.453	2.19	0.029	0.087	33.5	0.101	fixed
II+ID/DD	overall	56	8619/15718	1.131	1.008–1.270	2.10	0.036	0.092	60.5	<0.001	random
	overall in HWE	47	7219/14105	1.138	0.963–1.344	1.52	0.129	0.194	60.9	<0.001	random
	late onset	18	2664/3322	1.156	1.026–1.304	2.38	0.017	0.020	47.5	0.013	fixed
	late onset in HWE	15	2133/2625	1.138	0.996–1.299	1.90	0.057	0.114	20.7	0.222	fixed
II/ID+DD	overall	56	8619/15718	1.083	0.963–1.218	1.33	0.183	0.183	57.8	<0.001	random
	overall in HWE	47	7219/14105	1.067	0.937–1.214	0.97	0.330	0.330	57.3	<0.001	random
	late onset	18	2664/3322	1.272	1.120–1.444	3.71	<0.001	<0.001	43.8	0.024	fixed
	late onset in HWE	15	2133/2625	1.162	0.924–1.462	1.28	0.200	0.200	51.7	0.011	random

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OR: odds ratio; 95% CI: 95% confidence interval; z: test for overall effect; I²: I² value for heterogeneity test.

FDR: adjusted p value using Benjamini-Hochberg (BH) method.

p(Q): p value of the Dersimonian and Laird’s Q test for heterogeneity evaluation.

In subgroup analysis restricted to late-onset individuals, our investigation indicated significant associations between rs1799752 polymorphism and risk to AD using allelic comparison, additive model (II vs. ID, II vs. DD), dominant model and recessive model (II vs. ID + DD). In brief, rs1799752 I conferred increased risk to AD compared to the D allele with an odds ratio of 1.154 (95% CI = 1.028–1.295, p = 0.015, FDR = 0.020). In genotype analysis, the I homozygotes showed higher susceptibility for developing AD compared to the D homozygotes (OR = 1.308, 95% CI = 1.120–1.528, p = 0.001, FDR = 0.003). Moreover, the risk for AD was significantly higher in the I homozygotes than in the D carriers (OR = 1.272, 95% CI = 1.120–1.444, p < 0.001, FDR < 0.001, Fig 2). In cumulative meta-analysis for the I homozygotes versus the D homozygotes, after only 3 of the 18 cohorts had been studied, the fixed-effect odds ratio became larger than 1 and remained so thereafter (Fig 3). However, after excluding 3 cohorts deviated from HWE [30, 31, 55], no positive results could be identified in any genetic model. Subgroup analyses of large sample size cohorts and small sample size cohorts obtained similar results.

Fig 2 — I represents the insertion allele, and D represents the deletion allele. The size of the gray box is proportional to the weight of the corresponding study. The pooled estimate is displayed as a diamond. Bars, 95% confidence interval (CI).

Fig 3 — Each study was used as an information step. The vertical dotted line is the summary odds ratio. Bars, 95% confidence interval (CI).

We also compared ethnic difference among East Asians (Chinese and Japanese), North Europeans and populations of South European descent (Mediterranean and Middle Eastern). Respectively, 15 studies carried out among East Asians, 16 among North Europeans and 18 in cohorts of South European descent. East Asians had higher I allele frequency compared to those of European descent (p < 0.001). In East Asians, the significant associations between rs1799752 and AD susceptibility were revealed using allelic comparison, additive model (II vs. ID, II vs. DD), and recessive model. Nevertheless, none of them was robust enough to withstand the FDR adjustment, suggesting the positive results were weak evidence of true associations. In North Europeans, the I allele conferred increased risk to AD compared to the D allele (OR = 1.096, 95% CI = 1.021–1.178, p = 0.012, FDR = 0.039). Meanwhile, the I homozygotes showed higher susceptibility to AD compared with the D homozygotes (OR = 1.202, 95% CI = 1.040–1.390, p = 0.013, FDR = 0.039). After excluding those cohorts not in accordance with HWE, the positive associations in North Europeans were more obvious, not only under allelic comparison and homozygotes comparison, but also using additive model (ID vs. DD: OR = 1.266, 95% CI = 1.045–1.534, p = 0.016, FDR = 0.024) and dominant model (II + ID vs. DD: OR = 1.197, 95% CI = 1.062–1.350, p = 0.003, FDR = 0.018, Fig 4). With regard to populations of South European descent, no significant association was found under all comparisons (Table 4).

Fig 4 — I represents the insertion allele, and D represents the deletion allele. The size of the gray box is proportional to the weight of the corresponding study. The pooled estimate is displayed as a diamond. Bars, 95% confidence interval (CI).

Table 4. Pooled odds ratios of rs1799752 I/D polymorphism and AD risk by ethnic group.

A
	East Asians					North Europeans					South European descent (all in HWE)
	(1848/2400^a, 58.2±11.3%^b)					(3019/8986, 46.1±3.5%)					(2932/3542, 41.0±5.7%)
	OR	95% CI	p	I ²	FDR	OR	95% CI	p	I ²	FDR	OR	95% CI	p	I ²	FDR
I/D	1.308	1.021–1.675	0.034	84.8%	0.068	1.096	1.021–1.178	0.012	22.1%	0.039	0.956	0.888–1.029	0.232	45.7%	0.363
II/ID	1.330	1.001–1.767	0.049	73.2%	0.074	1.072	0.943–1.219	0.289	41.0%	0.289	0.916	0.791–1.061	0.242	0.0%	0.363
ID/DD	1.250	0.874–1.786	0.221	67.4%	0.221	1.209	0.989–1.478	0.064	60.2%	0.096	0.984	0.879–1.101	0.775	24.9%	0.775
II/DD	1.676	1.040–2.701	0.034	81.2%	0.068	1.202	1.040–1.390	0.013	23.0%	0.039	0.910	0.781–1.061	0.228	29.0%	0.363
II+ID/DD	1.407	0.951–2.082	0.087	76.7%	0.104	1.209	1.013–1.444	0.035	54.0%	0.070	0.963	0.866–1.071	0.486	39.8%	0.583
II/ID+DD	1.419	1.044–1.928	0.025	80.3%	0.068	1.114	0.987–1.258	0.081	25.0%	0.097	0.910	0.793–1.045	0.183	13.5%	0.363
B
	East Asians in HWE					North Europeans in HWE					South European descent in HWE
	(1189/1669, 57.7±13.5%)					(2780/8644, 46.0±3.7%)					(2932/3542, 41.0±5.7%)
	OR	95% CI	p	I ²	FDR	OR	95% CI	p	I ²	FDR	OR	95% CI	p	I ²	FDR
I/D	1.467	1.043–2.062	0.028	87.3%	0.056	1.102	1.022–1.188	0.012	26.7%	0.024	0.956	0.888–1.029	0.232	45.7%	0.363
II/ID	1.518	1.053–2.189	0.025	75.7%	0.056	1.016	0.888–1.163	0.814	25.4%	0.814	0.916	0.791–1.061	0.242	0.0%	0.363
ID/DD	1.257	0.776–2.037	0.352	69.9%	0.352	1.266	1.045–1.534	0.016	51.6%	0.024	0.984	0.879–1.101	0.775	24.9%	0.775
II/DD	2.002	1.035–3.872	0.039	83.5%	0.059	1.207	1.036–1.405	0.016	28.1%	0.024	0.910	0.781–1.061	0.228	29.0%	0.363
II+ID/DD	1.554	0.906–2.664	0.109	79.0%	0.131	1.197	1.062–1.350	0.003	48.9%	0.018	0.963	0.866–1.071	0.486	39.8%	0.583
II/ID+DD	1.644	1.089–2.482	0.018	83.4%	0.056	1.077	0.948–1.223	0.257	17.1%	0.308	0.910	0.793–1.045	0.183	13.5%	0.363

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^a cases/controls

^b I frequencies in controls.

OR: odds ratio; 95% CI: 95% confidence interval; z: test for overall effect; I²: I² value for heterogeneity test.

FDR: adjusted p value using Benjamini-Hochberg (BH) method.

Seven studies provided data about rs1799752 polymorphism and ε2/ε3/ε4 genotypes. With regard to AD susceptibility, no significant association was identified in both APOE ε4 positive and negative subgroups. However, after exclusion of HWE-deviated samples [27, 51], in the I homozygotes and the D homozygotes, the presence of APOE ε4 increased the risk of AD 2.84-fold (95% CI = 1.825–4.418, p < 0.001) and 7.06-fold (95% CI = 3.963–12.571, p < 0.001), respectively.

rs1800764 T/C and AD risk

Analysis for rs1800764 T/C polymorphism was available on 20 samples, including 6371 cases and 6768 controls. All the above investigations were published in English. In total, the T carriers demonstrated increased risk for developing AD compared with the C homozygotes, but the FDR value is insignificant (OR = 1.099, 95% CI = 1.005–1.201, p = 0.038, FDR = 0.114). Similar results were found in large sample size studies and after excluding studies not in accordance with HWE (Table 5). Since there was insufficient information to allow subgroup analysis in East Asians or in populations of South European descent, meta-analysis was only performed in all cohorts of European descent. Significant associations were revealed in populations of European descent under allelic comparison (T vs. C: OR = 1.063, 95% CI = 1.008–1.120, p = 0.023, FDR = 0.046) and additive model (TT vs. CC: OR = 1.136, 95% CI = 1.022–1.262, p = 0.018, FDR = 0.046). Furthermore, The T carriers conferred increased risk to develop AD compared with the C homozygotes (OR = 1.116, 95% CI = 1.018–1.222, p = 0.019, FDR = 0.046, Fig 5). No significant association was revealed in all comparisons in late-onset subgroup analysis. Nevertheless, after excluding 2 cohorts not satisfying HWE [71], all the associations became insignificant.

Table 5. Pooled odds ratios for rs1800764 polymorphism and AD susceptibility.

Comparisons	Data	No. of cohorts	Cases/controls	OR	95% CI	z	p	FDR	I² (%)	p(Q)	Effect model
T/C	overall	20	6371/6768	1.047	0.995–1.102	1.75	0.080	0.120	20.1	0.205	fixed
	overall in HWE	18	5978/6476	1.050	0.996–1.107	1.83	0.068	0.160	17.2	0.138	fixed
	European descent	18	6148/6173	1.063	1.008–1.120	2.27	0.023	0.046	0.0	0.494	fixed
	European descent in HWE	16	5755/5881	1.067	1.011–1.126	2.36	0.018	0.060	5.1	0.395	fixed
TT/TC	overall	20	6371/6768	1.007	0.928–1.094	0.18	0.861	0.861	2.4	0.427	fixed
	overall in HWE	18	5978/6476	1.032	0.948–1.124	0.73	0.464	0.464	0.0	0.759	fixed
	European descent	18	6148/6173	1.028	0.944–1.119	0.64	0.522	0.522	0.0	0.574	fixed
	European descent in HWE	16	5755/5881	1.056	0.968–1.153	1.23	0.219	0.219	0.0	0.928	fixed
TC/CC	overall	20	6371/6768	1.097	0.998–1.206	1.92	0.055	0.114	12.3	0.301	fixed
	overall in HWE	18	5978/6476	1.073	0.974–1.183	1.43	0.153	0.230	0.0	0.572	fixed
	European descent	18	6148/6173	1.105	1.003–1.217	2.02	0.044	0.066	16.5	0.256	fixed
	European descent in HWE	16	5755/5881	1.080	0.978–1.193	1.52	0.128	0.154	0.0	0.514	fixed
TT/CC	overall	20	6371/6768	1.105	0.997–1.224	1.91	0.057	0.114	15.0	0.267	fixed
	overall in HWE	18	5978/6476	1.105	0.994–1.228	1.85	0.065	0.160	23.0	0.182	fixed
	European descent	18	6148/6173	1.136	1.022–1.262	2.37	0.018	0.046	0.0	0.512	fixed
	European descent in HWE	16	5755/5881	1.137	1.120–1.267	2.32	0.020	0.060	5.5	0.390	fixed
TT+TC/CC	overall	20	6371/6768	1.099	1.005–1.201	1.08	0.038	0.114	16.8	0.244	fixed
	overall in HWE	18	5978/6476	1.085	0.990–1.189	1.75	0.080	0.160	14.3	0.283	fixed
	European descent	18	6148/6173	1.116	1.018–1.222	2,35	0.019	0.046	12.5	0.305	fixed
	European descent in HWE	16	5755/5881	1.102	1.003–1.210	2.02	0.043	0.086	9.6	0.344	fixed
TT/TC+CC	overall	20	6371/6768	1.034	0.957–1.117	0.84	0.398	0.478	7.4	0.364	fixed
	overall in HWE	18	5978/6476	1.052	0.971–1.140	1.25	0.212	0.254	0.2	0.452	fixed
	European descent	18	6148/6173	1.058	0.977–1.146	1.39	0.164	0.197	0.0	0.647	fixed
	European descent in HWE	16	5755/5881	1.080	0.994–1.172	1.83	0.068	0.102	0.0	0.804	fixed

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OR: odds ratio; 95% CI: 95% confidence interval; z: test for overall effect; I²: I² value for heterogeneity test.

FDR: adjusted p value using Benjamini-Hochberg (BH) method.

p(Q): p value of the Dersimonian and Laird’s Q test for heterogeneity evaluation.

Fig 5 — The size of the gray box is proportional to the weight of the corresponding study. The pooled estimate is displayed as a diamond. Bars, 95% confidence interval (CI).

Other polymorphisms and AD risk

23 studies containing 9783 cases and 16890 controls studied the association between rs4343 A/G polymorphism and AD risk. 20 studies including 5973 cases and 13044 controls evaluated the correlation of rs4291 A/T polymorphism and AD susceptibility. For rs4309 C/T, 4 studies involving 1187 cases and 1056 controls were included. All of those investigations were published in English. No significant associations were identified in terms of allelic comparison for all these three polymorphisms (rs4343 A vs. G: OR = 1.002, 95% CI = 0.926–1.084, p = 0.962, FDR = 0.962; rs4291 A vs. T: OR = 1.025, 95% CI = 0.973–1.080, p = 0.360, FDR = 0.540; rs4309 C vs. T: OR = 1.072, 95% CI = 0.758–1.517, p = 0.694, FDR = 0.790). In further genotype comparison, we still did not reveal any significant association for the three polymorphisms, no matter using additive model, dominant model or recessive model. Subgroup analysis restricted to late-onset individuals, populations of European descent, or large sample size studies for rs4343 A/G and rs4291 A/T polymorphisms obtained similar results.

Publication bias

Both the Begg-Mazumdar test and the Egger’s regression asymmetry test were conducted to evaluate potential publication bias. For all the above polymorphisms, the p values of Begg-Mazumdar tests and Egger’s tests were greater than 0.05, suggesting no evidence was found for the presence of publication bias.

Discussion

In this comprehensive meta-analysis about ACE polymorphisms and AD susceptibility on the basis of all available updated studies published in both Chinese and English, 82 cohorts were involved, comprising more than 47000 genotyped cases and controls. Our results demonstrated the significant associations between rs1799752 polymorphism and AD susceptibility in North Europeans, but not in East Asians and populations of South European descent, suggesting the ethnic difference of the role that rs1799752 polymorphism played on AD risk. However, our results did not support the associations between rs4343, rs4291 and rs4309 polymorphisms and susceptibility to AD.

Meta-analysis has been considered as a useful tool to achieve more precise estimation of the effect of candidate polymorphism in multifactorial diseases, such as AD. Small sample size, in combination with modest effect, might lead to low statistical power of individual study, which is the most likely explanation for the controversial results of previous investigations. Meta-analysis is one strategy to increase sample size in an attempt to reduce random error which might produce false-positive or false-negative associations. Since deviation from HWE usually means mistyping or selection bias [85], we also excluded those samples not satisfying HWE in controls in sensitivity analysis to increase the accuracy of our results.

For rs1799752 polymorphism, compared to previous meta-analyses performed in 2004 and 2005 [49, 86], we included more than 20 new studies and covered all articles published in Chinese. In overall analyses, before multiple comparison adjustment, our study indicated that the I allele conferred increased risk to AD compared with the D allele and the D homozygotes were at reduced risk of AD compared to the I carriers, which were in accordance with results from the two previous meta-analyses. To avoid false positive in multiple comparisons, we applied the widely accepted FDR adjustment in our study [87]. Since no significant association passed the FDR adjustment, we believed that the associations were not robust enough. In another investigation adopted false-positive report probability (FPRP) to control false-positive findings, the authors obtained similar results as those from our study [88].

In subgroup analysis, significant associations between rs1799752 polymorphism and late-onset AD risk were revealed using allelic comparison, additive model, dominant model and recessive model. However, as well as those identified for rs1800764 in populations of European descent, after excluding studies not satisfying HWE, no positive results could be obtained, indicating the instability of the associations. Thus, in the future, well-designed large sample size studies to provide more forceful evidence for the possible associations are required.

When cohorts were stratified by ethnic background, significant difference was identified among East Asians, North Europeans and populations of South European descent with regard to rs1799752 polymorphism. East Asians had higher I allele frequencies compared to populations of European descent in controls. Furthermore, the most robust and consistent associations between rs1799752 polymorphism and risk to AD were identified particularly in North Europeans. We attributed the difference of results among Europeans and Asians mainly to the difference of genetic background. However, no comparable investigations have been carried out with regard to mechanisms underlying rs1799752 polymorphism and AD development between different ethnics, which still need further research to clarify. Before FDR adjustment, our results of East Asians were in accordance with those of previous meta-analysis performed in Chinese samples [89]. The ethnic difference of the associations between rs1799752 polymorphism and AD risk should be considered in the design of future studies.

One copy of the APOE ε4 allele may increase the risk of AD by 2–6 times [90]. In our study, in the D homozygotes, the presence of APOE ε4 increased the risk of AD around 7.06-fold, much higher than that identified in the I homozygotes. However, only 5 studies satisfying HWE provided data about rs1799752 polymorphism and APOE ε4 status, we still need more information to draw safe conclusions about the possible interaction between APOE ε4 and rs1799752 polymorphism.

In overall analyses for rs1799752 polymorphism, high heterogeneity was identified in different comparisons. After ethnic stratification, high heterogeneity was removed in both North Europeans and cohorts of South European descent, but not in East Asians, suggesting the existence of other confounding factors responsible for heterogeneity. Besides ethnic background, other sources accounting for heterogeneity include differences in sample selection (e.g., age of onset, diagnosis criteria), or in methods (e.g., genotyping methods), or it may be due to interaction with other risk factors (e.g., APOE ε4 status). When we restricted the study populations to late-onset individuals, heterogeneity among studies reduced. While stratification by APOE ε4 status nearly removed all the heterogeneity. Our results suggested that age of onset and interaction with APOE ε4 status also contributed to the high heterogeneity in the analyses of rs1799752 polymorphism.

There are several limitations of our investigation. Firstly, publication bias against reporting negative associations might affect our results. Secondly, no other language article regarding ACE polymorphisms and risk to AD was found besides those in English and Chinese. However, some articles cloud be published in journals not on the international journal catalogs, leading to potential language bias. Thirdly, owing to lack of original data, further adjustments by other covariables, such as gender or cardiovascular complications, could not be performed.

Conclusions

In summary, ACE rs1799752 polymorphism is associated with risk to AD in North Europeans. The relationships between rs1799752 and late-onset AD susceptibility, as well as rs1800764 and AD risk in populations of European descent, still need further studies to illustrate. While rs4343, rs4291 and rs4309 polymorphisms are unlikely to be major factors in AD development in our research.

Supporting information

S1 Checklist. PRISMA 2020 checklist.

(DOCX)

Click here for additional data file.^{(28.1KB, docx)}

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This study was supported by grants from the National Natural Science Foundation of China (81301046). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0260498.r001

Decision Letter 0

Zhicheng Lin

28 Jul 2021

PONE-D-21-18823

Angiotensin-Converting Enzyme Polymorphisms AND Alzheimer’s Disease Susceptibility: An Updated Meta-Analysis

PLOS ONE

Dear Dr. Xin,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #1: This meta analysis by Dr. Xin concluded studies about ACE and AD, aiming to aimed to clarify the effect of ACE polymorphisms on AD risk. The whole research is quite comprehensive and objective, but there are still some shortcomings.Here are some of my suggestions.

1.Some viewpoints need more supporting materials or references, such as “the ε4 allele

accounts for an estimated 45% to 60% of the genetic susceptibility to AD”

2.“Angiotensin converting enzyme (ACE) is an important component of the renin-angiotensin

system (RAS), which mainly acts on promoting the formation of Angiotensin II (Ang II) from

Angiotensin I (Ang I). Recently, many evidences supported that ACE participated in the pathogenesis of AD. As a membrane-bound zinc metalloprotease, ACE played an important role in Aβ degradation. ” should be revised as “Recently, many evidences supported that ACE participated in the pathogenesis of AD. As a membrane-bound zinc metalloprotease, ACE played an important role in Aβ degradation. Angiotensin converting enzyme (ACE) is an important component of the renin-angiotensin system (RAS), which mainly acts on promoting the formation of Angiotensin II (Ang II) from Angiotensin I (Ang I).”. It reads more fluent and logistic.

3.Some sentences were obscure, like “We also stratified the study cohorts, when possible, according to the age of onset, ethnic background and APOE ε4 status.” The relationship between ACE and APOEε4 should be illustrated more.

4.Are there any RCTs (the most convincing type in meta analysis) involved in this research? If yes, pls add one or two sentences in “study election”. If not, pls also explain the reason.

5.In the conclusion, the sentence “While rs4343, rs4291 and rs4309 polymorphisms are unlikely to be major factors in AD development” sounds kind of absolute. It could be better when add “in our/this research” in the end.

Reviewer #2: Xin et al., described their findings in literature meta-analyses of genetic polymorphisms of ACE and indicated that the better associations between rs1799752 polymorphism and risk to AD in North Europeans. But the rs4343, rs4291 and rs4309 polymorphisms are not significantly correlated with AD development. Overall, this paper described well, but still have some problems and questions need further clarification and revision.

Comments:

1. Please identify what is I and D in the Abstract.

2. In the introduction, the authors described “However, the ε4 allele

accounts for an estimated 45% to 60% of the genetic susceptibility to AD, which is neither necessary nor sufficient to cause the disease”. But there are still some references supporting APOE ε4 which increases risk for Alzheimer's disease and is also associated with an earlier age of disease onset. Please clarify.

3. In literature search, the authors indicated that no language restriction. However, normally a better selection criterion is the literature written in English.

4. In study selection, the authors should try to select the cohort with higher numbers of subjects. Because they mentioned in the introduction that “some discrepancies may be related to the small sample size of individual studies”.

5. The authors should try to link the correlation between rs1799752 polymorphism or others and their potential effects on the function of ACE.

6. It is suggested to discuss why North Europeans compared to East Asians carrying rs1799752 polymorphism are more susceptible to AD occurrence.

**********

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Reviewer #1: Yes: Jingwen Li

Reviewer #2: No

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PLoS One. 2021 Nov 24;16(11):e0260498. doi: 10.1371/journal.pone.0260498.r002

Author response to Decision Letter 0

30 Sep 2021

Replies to Academic Editor

We are very grateful for your careful work earnestly. We considered every comment and suggestion of you and made cautious revision accordingly as follows:

Comment 1: Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Response: We have revised our manuscript according to the PLOS ONE style templates to make it meet the style requirements, including those for file naming.

Comment 2: Please include the tables to within the manuscript.

Response: The tables have been included within the manuscript.

Comment 3: Please change ‘Caucasian’to ‘white’ or ‘of European descent’.

Response: According to your suggestion, ‘of European descent’ or ‘Europeans’ has been used to substitute ‘Caucasian’ in the revised manuscript.

Comment 4: Please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

Response: Thank you for your careful checks. We have corrected the grant number in ‘Funding Information’ section according to your positive comment.

Comment 5: Please amend your list of authors on the manuscript to ensure that each author is linked to an affiliation.

Response: We have amended our list of authors to ensure that each author is linked to an affiliation in the revised version.

Comment 6: Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly.

Response: We have added captions for Supporting Information files at the end of our manuscript and updated in-text citations to match accordingly.

Replies to Reviewer 1

We would like to express our sincere thanks to you for your valuable suggestions and comments, which enable us to greatly improve the quality of our manuscript. The revised parts that correspond to the comments are listed as follows:

Comment 1: Some viewpoints need more supporting materials or references, such as “the ε4 allele accounts for an estimated 45% to 60% of the genetic susceptibility to AD”

Response: We totally agree with your suggestion. The statement of “the ε4 allele accounts for an estimated 45% to 60% of the genetic susceptibility to AD” has been corrected. We rewrote this part as “Presence of APOE ε4 allele increases risk of AD with a dose-dependent manner, and might lead to an earlier age of disease onset. The frequency of APOE ε4 in AD patients varied among different ethnics groups, ranging from around 40% to 60%, compared to 20%~25% in controls.” We think this modification help us express our viewpoint more clearly and accurately. In addition, we also added two references to support this viewpoint. (seen in the 2nd paragraph of Introduction)

1. Alex Ward, Sheila Crean, Catherine J Mercaldi, Jenna M Collins, Dylan Boyd, Michael N Cook, et al. Prevalence of apolipoprotein E4 genotype and homozygotes (APOE 4/4) among patients diagnosed with Alzheimer's disease: a systematic review and meta-analysis. Neuroepidemiology. 2012;38(1):1-17. DOI: 10.1159/000334607. PMID: 22179327. (Reference 4 in the manuscript)

2. Verghese PB, Castellano JM, Holtzman DM. Apolipoprotein E in Alzheimer's disease and other neurological disorders. Lancet Neurol. 2011;10(3):241-52. DOI: 10.1016/S1474-4422(10)70325-2. PMID: 21349439. (Reference 5 in the manuscript)

Comment 2: “Angiotensin converting enzyme (ACE) is an important component of the renin-angiotensin system (RAS), which mainly acts on promoting the formation of Angiotensin II (Ang II) from Angiotensin I (Ang I). Recently, many evidences supported that ACE participated in the pathogenesis of AD. As a membrane-bound zinc metalloprotease, ACE played an important role in Aβ degradation.” should be revised as “Recently, many evidences supported that ACE participated in the pathogenesis of AD. As a membrane-bound zinc metalloprotease, ACE played an important role in Aβ degradation. Angiotensin converting enzyme (ACE) is an important component of the renin-angiotensin system (RAS), which mainly acts on promoting the formation of Angiotensin II (Ang II) from Angiotensin I (Ang I).”.

Response: We appreciate your detailed comment. We have revised this part according to your kind suggestion. Now It reads more fluent and logistic. (seen in the 3rd paragraph of Introduction)

Comment 3: Some sentences were obscure, like “We also stratified the study cohorts, when possible, according to the age of onset, ethnic background and APOE ε4 status.” The relationship between ACE and APOE ε4 should be illustrated more.

Response: We agree with your assessment. We have incorporated your comment in the last paragraph of the introduction part. We added two references to support the possible relationship between ACE and APOE ε4, as well as to clarify why we stratified the study cohorts according to APOE ε4 status: “Since some recent evidence suggested that the presence of APOE ε4 influence the behavioural effects of ACE I/D polymorphism in AD, and the protective effects of ACE inhibitors or angiotensin receptor blockers on cognitive decline correlated with APOE ε4 carrier status, we also performed subgroup analyses according to APOE ε4 carrier status if sufficient data could be obtained”. (seen in the last paragraph of Introduction)

1. Oliveira FF, de Almeida SS, Smith MC, Bertolucci PHF. Behavioural effects of the ACE insertion/deletion polymorphism in Alzheimer's disease depend upon stratification according to APOE-ε4 carrier status. Cogn Neuropsychiatry. 2021;26(4):293-305. DOI: 10.1080/13546805.2021.1931085. PMID: 34034613 (Reference 12 in the manuscript)

2. Ouk M, Wu CY, Rabin JS, Jackson A, Edwards JD, Ramirez J, The use of angiotensin-converting enzyme inhibitors vs. angiotensin receptor blockers and cognitive decline in Alzheimer's disease: the importance of blood-brain barrier penetration and APOE ε4 carrier status. Alzheimers Res Ther. 2021 Feb 11;13(1):43. DOI: 10.1186/s13195-021-00778-8. PMID: 33573702 (Reference 13 in the manuscript)

Comment 4: Are there any RCTs (the most convincing type in meta-analysis) involved in this research? If yes, pls add one or two sentences in “study election”. If not, pls also explain the reason.

Response: You have raised an important concern, and we believe that RCTs are the most convincing type in meta-analysis. However, randomized controlled design might be more suitable for clinical trials rather than gene polymorphism studies of patients and controls. We could not identify any RCTs in electronic database search in the present investigation. We have added illustration to this point as follows in Study selection: “Since all the included studies were gene polymorphism investigations in patients and controls, which were not suitable for randomized controlled design, no randomized controlled trial (RCT) could be identified and involved in our research.” (seen in the 1st paragraph of Study selection in Materials and methods)

Comment 5: In the conclusion, the sentence “While rs4343, rs4291 and rs4309 polymorphisms are unlikely to be major factors in AD development” sounds kind of absolute. It could be better when add “in our/this research” in the end.

Response: We agree with your advice. We have added the words “in our research” in the end of this sentence in the revised manuscript. (seen in Conclusions)

Sincerely yours,

Xiao-Yu Xin

Replies to Reviewer 2

Thanks a lot for your generous and detailed comments. Your suggestions provide an important direction for us to revise our paper. We itemized our point-by-point responses to your comments as follows:

Comment 1: Please identify what is I and D in the Abstract.

Response: Thank you for your reminding, we have identified what is I and D in Abstract in the revised version: “the insertion (I) allele conferred increased risk to AD compared to the deletion (D) allele”. (seen in Abstract)

Comment 2: In the introduction, the authors described “However, the ε4 allele accounts for an estimated 45% to 60% of the genetic susceptibility to AD, which is neither necessary nor sufficient to cause the disease”. But there are still some references supporting APOE ε4 which increases risk for Alzheimer's disease and is also associated with an earlier age of disease onset. Please clarify.

Response: Thank you for pointing out the potential for misunderstanding. We have adjusted the text to be clearer. According to your nice suggestion, we revised this part as follows: “Presence of APOE ε4 allele increases risk of AD with a dose-dependent manner, and might lead to an earlier age of disease onset. The frequency of APOE ε4 in AD patients varied among different ethnic groups, ranging from around 40% to 60%, compared to 20%~25% in controls. Therefore, the presence of ε4 is neither necessary nor sufficient to cause the disease, indicating the participant of other heritable risk factors underlying the development of AD”. We also added two references to support the above statements. (seen in the 2nd paragraph of Introduction)

Comment 3: In literature search, the authors indicated that no language restriction. However, normally a better selection criterion is the literature written in English.

Response: You have raised an interesting concern. We believe that high quality investigations usually published in English. However, the strength of meta-analysis depends on combining all available published data to increase statistical power, including those not written in English. Therefore, beside PubMed, Embase and Alzgene, we also searched CNKI (China National Knowledge Infrastructure) for associated studies, which mainly contains literature written in Chinese. Moreover, some high- quality meta-analyses used CNKI for literature search too, such as those published in Lancet series [1,2]. In addition, we used Newcastle-Ottawa Scale (NOS) to assess the methodological quality of each involved study, which has been widely used in meta-analysis (Table 1) [3]. In our analyses for rs1799752, 7 studies were published in Chinese, and others in English. According to your nice suggestion, after broad analysis, we performed analyses particularly in studies written in English. Similar results were obtained after excluding literature in Chinese. We supplied the above results in our revised manuscript: “When analyses were performed particularly in investigations published in English, no reliable associations were identified either.” (seen in the 1st paragraph of rs1799752 I/D and AD risk in Results). For the other several polymorphisms, all the included investigations were written in English. (seen in the 1st paragraph of rs1800764 T/C and AD risk in Results, the 1st paragraph of Other polymorphisms and AD risk in Results)

1. Slee A, Nazareth I, Bondaronek P, Liu Y, Cheng Z, Freemantle N. Pharmacological treatments for generalised anxiety disorder: a systematic review and network meta-analysis. Lancet. 2019;393(10173):768-777. DOI: 10.1016/S0140-6736(18)31793-8. PMID: 30712879

2. Funk AL, Lu Y, Yoshida K, Zhao T, Boucheron P, van Holten J, et al. Efficacy and safety of antiviral prophylaxis during pregnancy to prevent mother-to-child transmission of hepatitis B virus: a systematic review and meta-analysis. Lancet Infect Dis. 2021;21(1):70-84. DOI: 10.1016/S1473-3099(20)30586-7. PMID: 32805200

3. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603-5. DOI:10.1007/s10654-010-9491-z. PMID:20652370 (Reference 14 in the manuscript)

Comment 4: In study selection, the authors should try to select the cohort with higher numbers of subjects. Because they mentioned in the introduction that “some discrepancies may be related to the small sample size of individual studies”.

Response: Thank you for pointing out the ambiguous statement in our article. We meant that small sample size, in combination with modest effect, might contribute to low statistical power, which was an important reason responsible for the diversity of previous results. None of individual studies could show more sufficient statistical power than the results of meta-analysis. Because the strength of meta-analysis is the accumulation of all the available published data to increase statistical power, largely addressing the issue of sample size. We have adjusted the text to be clearer as follows: “While meta-analysis is a well-established means to quantitatively synthesize all association data across studies to reduce heterogeneity and identify minor genetic effects, which largely addressing the issue of sample size.” (seen in the 4th paragraph of Introduction). In addition, according to your comment, we compared pooled ORs of large sample size subgroup (more than 300 cases and controls in total) and small sample size subgroup (less than 300 cases and controls in total) when possible, but no significant difference was identified. We also added this part to the revised manuscript. (seen in the last paragraph of Statistical analysis in Materials and methods, the 2nd paragraph of rs1799752 I/D and AD risk in Results, the 1st paragraph of rs1800764 T/C and AD risk in Results, the 1st paragraph of Other polymorphisms and AD risk in Results)

Comment 5: The authors should try to link the correlation between rs1799752 polymorphism or others and their potential effects on the function of ACE.

Response: Thank you for your kind reminding. We have added the potential effects of rs1700752 polymorphism on ACE function in the 4th paragraph of introduction as follows: “The I/D genotype is regarded as a determinant of ACE expression levels in plasma, cells and tissues. Approximately 50% variability in plasma levels of ACE depends on the rs1799752 polymorphism”. We also added 2 references to support the possible correlation. Unfortunately, we found few studies reporting the functions of other polymorphisms. We only know that “rs1800764 and rs4291 located in the regulatory region of ACE gene, while rs4343 in the exotic region.” Though function of the above polymorphisms is outside our investigation, we believe that you have raised a significant direction in future consideration. (seen in the 4th paragraph of Introduction)

1. Cafiero C, Rosapepe F, Palmirotta R, Re A, Ottaiano MP, Benincasa G, et al. Angiotensin System Polymorphisms' in SARS-CoV-2 Positive Patients: Assessment Between Symptomatic and Asymptomatic Patients: A Pilot Study. Pharmgenomics Pers Med. 2021;14:621-629. DOI: 10.2147/ PGPM.S303666. PMID: 34079337. (Reference 9 in the manuscript)

2. Ghafouri-Fard S, Noroozi R, Omrani MD, Branicki W, Pośpiech E, Sayad A, et al. Angiotensin converting enzyme: A review on expression profile and its association with human disorders with special focus on SARS-CoV-2 infection. Vascul Pharmacol. 2020;130:106680. DOI: 10.1016/j.vph.2020. 106680. PMID: 32423553. (Reference 10 in the manuscript)

Comment 6: It is suggested to discuss why North Europeans compared to East Asians carrying rs1799752 polymorphism are more susceptible to AD occurrence.

Response: We think that ethnic genetic background difference is the main reason responsible for the difference of pooled ORs between North Europeans and East Asians. For example, the prevalence of I allele in Asian controls is higher than in European controls not only in our study but also in a recent report [1]. But the underlying reason hasn’t been identified yet, which still need further investigation to clarify. Thanks to your constructive advice, we have added this part in the 5th paragraph of Discussion as follows: “We attributed the difference of results among Europeans and Asians mainly to the difference of genetic background. However, no comparable investigations have been carried out with regard to mechanisms underlying rs1799752 polymorphism and AD development between different ethnics, which still need further research to clarify.”(seen in the 5th paragraph of Discussion)

1. Hatami N, Ahi S, Sadeghinikoo A, Foroughian M, Javdani F, Kalani N, et al. Worldwide ACE (I/D) polymorphism may affect COVID-19 recovery rate: an ecological meta-regression. Endocrine. 2020;68(3):479-484. DOI: 10.1007/s12020-020-02381-7. PMID: 32542429

Best wishes,

Xiao-Yu Xin

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PLoS One. doi: 10.1371/journal.pone.0260498.r003

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11 Nov 2021

Angiotensin-Converting Enzyme Polymorphisms AND Alzheimer’s Disease Susceptibility: An Updated Meta-Analysis

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15 Nov 2021

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Angiotensin-Converting Enzyme Polymorphisms AND Alzheimer’s Disease Susceptibility: An Updated Meta-Analysis

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PERMALINK

Angiotensin-converting enzyme polymorphisms AND Alzheimer’s disease susceptibility: An updated meta-analysis

Xiao-Yu Xin

Ze-Hua Lai

Kai-Qi Ding

Li-Li Zeng

Jian-Fang Ma

Roles

Abstract

Background

Methods

Results

Conclusions

Introduction

Materials and methods

Literature search

Study selection

Data extraction

Statistical analysis

Results

Eligible studies and candidate polymorphisms

Table 1. General characteristics of included studies in the present meta-analysis.

Table 2. Summary of ACE polymorphisms included in the present meta-analysis.

Fig 1. PRISMA flow diagram for literature search and study selection.

rs1799752 I/D and AD risk

Table 3. Pooled odds ratios for rs1799752 polymorphism and AD susceptibility.

Fig 2. Fixed-effects odds ratio (OR) for the association of ACE rs1799752 I/D polymorphism with late-onset AD susceptibility (II vs. ID+DD).

Fig 3. Cumulative meta-analysis of the relation between ACE rs1799752 I/D polymorphism and late-onset AD susceptibility (II vs DD).

Fig 4. Fixed-effects odds ratio (OR) for the association of ACE rs1799752 I/D polymorphism AD susceptibility in North Europeans in accordance with HWE (II + ID vs DD).

Table 4. Pooled odds ratios of rs1799752 I/D polymorphism and AD risk by ethnic group.

rs1800764 T/C and AD risk

Table 5. Pooled odds ratios for rs1800764 polymorphism and AD susceptibility.

Fig 5. Fixed-effects odds ratio (OR) for the association of ACE rs1800764 T/C polymorphism AD susceptibility in populations of European descent (TT+TC vs CC).

Other polymorphisms and AD risk

Publication bias

Discussion

Conclusions

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Zhicheng Lin

Roles

Author response to Decision Letter 0

Decision Letter 1

Zhicheng Lin

Roles

Acceptance letter

Zhicheng Lin

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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