Количественная роль гомоцистайна в многочисленных болезнях: систематический обзор исследований менделийской случайности.

Introduction

Homocysteine (Hcy), a sulfur-containing non-protein amino acid, serves as a metabolic intermediate between methionine and cysteine. While neither methionine nor cysteine is directly involved in protein synthesis, both play a crucial role in the methylation process. Hcy is a key component in methionine metabolism, ensuring stable methionine levels, which in turn support protein synthesis and DNA repair. It can be remethylated to methionine or converted into cysteine with the aid of certain B vitamins [ 1 ].

Beyond its metabolic role, Hcy exhibits multiple biological functions, including antioxidant and immune system regulation, all of which are essential for maintaining overall health [ 2 , 3 ]. Previous observational studies have established strong associations between Hcy and various diseases, such as neurodegenerative disorders [ 4 ], cardiovascular disease [ 5 ], venous thromboembolism [ 6 ], and cancer [ 7 ]. However, these studies are inherently limited by confounding factors and reverse causation, making it difficult to establish a causal relationship between Hcy and disease risk. Although Mendelian randomization (MR) is not entirely free from these limitations, it is less prone to such biases compared to conventional observational studies.

MR is a causal inference method based on the principles of genetics. The core idea is to use single nucleotide polymorphisms (SNPs) in the human genome as an instrumental variable to mimic the process of randomly assigning genotypes in Mendelian inheritance experiments, and thus to infer potential causal relationships between the exposure (as genetically proxied) and the outcome. MR studies rely on three major assumptions [ 8 ]:

The assumption of correlation –SNPs must be significantly associated with the exposure of interest. The assumption of independence –SNPs should be independent of confounding variables. The assumption of exclusivity –SNPs must influence the outcome solely through their effect on the exposure factor.

The assumption of correlation –SNPs must be significantly associated with the exposure of interest.

The assumption of independence –SNPs should be independent of confounding variables.

The assumption of exclusivity –SNPs must influence the outcome solely through their effect on the exposure factor.

Traditional observational studies are often susceptible to bias due to confounding factors and reverse causation, potentially leading to misleading conclusions. In contrast, MR leverages genetic variants as instrumental variables to mitigate these biases, thereby enhancing causal inference [ 9 ].

To the best of our knowledge, this study is the first comprehensive review and robustness assessment of MR-based research investigating the causal effects of Hcy on multiple diseases. The primary objective of this review is to systematically evaluate and synthesize existing evidence to provide robust support for the causal role of Hcy in disease development.

Methods

This systematic review adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [ 10 ]. The review protocol has been registered with PROSPERO (International Prospective Register of Systematic Reviews) and is available online under the identifier CRD42024549647.

Literature search and study selection

A comprehensive literature search was conducted in PubMed, the Cochrane Library, Embase, and Web of Science on May 30, 2024, following a pre-established search strategy. The search incorporated the term “Mendelian randomization” in combination with “homocysteine”, along with relevant synonyms and associated keywords. Database-specific filters were applied to include only studies involving human participants and published in English. Additionally, the reference lists of selected studies were manually screened to identify any potentially relevant literature that might have been omitted in the primary search. The detailed search strategies for each database are provided in Supplementary Material 1 .

Two independent investigators, both experienced in evidence-based medicine and Mendelian randomization research, conducted the study selection. They utilized EndNote X9.3.3 software to remove duplicates, screen articles, and extract relevant data based on predefined inclusion and exclusion criteria. The extracted data were subsequently cross-verified for accuracy. Any discrepancies or uncertainties were resolved through discussion with a third researcher to reach a consensus.

Eligibility criteria

This review considers studies that examine outcomes suggested to be causally associated with Hcy within an MR framework. The inclusion criteria were as follows:

Language and Population: Studies published in English and exclusively involving human participants. Study Design: Studies employing Mendelian randomization (MR) as the primary methodological approach. Exposure and Outcomes: Studies investigating the causal relationship between Hcy levels and various health outcomes.

Language and Population: Studies published in English and exclusively involving human participants.

Study Design: Studies employing Mendelian randomization (MR) as the primary methodological approach.

Exposure and Outcomes: Studies investigating the causal relationship between Hcy levels and various health outcomes.

Studies were excluded if they met any of the following criteria:

Study Type: Systematic reviews or meta-analyses. Relevance: Studies irrelevant to the research question or those using inappropriate exposure measures. Methodological Approach: Studies that did not employ Mendelian randomization analysis. Availability: Studies without accessible full texts.

Study Type: Systematic reviews or meta-analyses.

Relevance: Studies irrelevant to the research question or those using inappropriate exposure measures.

Methodological Approach: Studies that did not employ Mendelian randomization analysis.

Availability: Studies without accessible full texts.

Data extraction

A data extraction protocol, aligned with PRISMA guidelines, was established to ensure standardized and systematic data collection. Data extraction was conducted independently by two investigators with expertise in Mendelian randomization research. Following extraction, both investigators cross-verified the data for consistency. Any discrepancies or uncertainties were resolved through consultation with a third researcher to reach a consensus.

Extracted data from each study included the first author’s name, publication year, exposure variable, source of exposure data, exposure sample size, primary ancestry of exposure participants, outcome variable, source of outcome data, primary ancestry of outcome participants, outcome sample size, number of SNPs used, primary MR analysis method, odds ratios (ORs), and associated P -values.

For dichotomous outcome variables, if studies reported only beta coefficients, OR values were calculated using Formula 1 in R software (version 4.3.2), and their 95% confidence intervals were calculated using Formulas 2 and 3:

Formula 1: \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\:OR={e}^{\beta\:}$$\end{document} Formula 2: \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\:{95\text{\%}\:\text{C}\text{I}}_{\text{d}\text{o}\text{w}\text{n}}\:=\:{e}^{\beta\:-1.96\times\:SE}$$\end{document} Formula 3 is as follows: \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\:{95\text{\%}\:\text{C}\text{I}}_{\text{u}\text{p}}\:=\:{e}^{\beta\:+1.96\times\:SE}$$\end{document}

Formula 1: \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\:OR={e}^{\beta\:}$$\end{document}

Formula 2: \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\:{95\text{\%}\:\text{C}\text{I}}_{\text{d}\text{o}\text{w}\text{n}}\:=\:{e}^{\beta\:-1.96\times\:SE}$$\end{document}

Formula 3 is as follows: \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\:{95\text{\%}\:\text{C}\text{I}}_{\text{u}\text{p}}\:=\:{e}^{\beta\:+1.96\times\:SE}$$\end{document}

where SE represents the standard error of the beta value, and 1.96 is the critical value of the standard normal distribution at the 95% confidence level.

Quality assessment

To evaluate study quality, data extraction was conducted using a template designed based on the STROBE-MR (Strengthening the Reporting of Observational Studies in Epidemiology with Mendelian Randomization) criteria [ 11 – 12 ]. This template included 20 main items and 30 subitems for assessing MR study reporting quality. After converting quality assessment scores into percentages, the 20 studies included in our analysis were categorized according to their risk of bias:

High risk: Scores below 75%. Medium risk: Scores between 75% and 85%. 3Low risk: Scores above 85%.

High risk: Scores below 75%.

Medium risk: Scores between 75% and 85%.

3Low risk: Scores above 85%.

Findings

Screening of literature and evaluation of study quality

The search strategy identified 202 relevant studies. After excluding 111 duplicates and irrelevant articles, an additional 49 studies were eliminated following the title and abstract review. Full-text assessment led to the exclusion of 9 more studies: 1 was not a systematic review, 2 were irrelevant or had inappropriate exposure, 2 were not Mendelian randomization analyses, 2 did not utilize MR methodology, and 2 had inaccessible full texts. Ultimately, 33 studies [ 13 – 45 ] met the pre-established criteria for inclusion in the quantitative synthesis (as shown in Fig.  1 ).

Fig. 1 Flowchart of search results and study retrieval

Flowchart of search results and study retrieval

Supplementary Material 2 details the quality assessment outcomes of the included studies. While all studies explicitly identified MR as the study design in their titles and abstracts and systematically addressed key methodological components—including research rationale, objectives, key findings, study settings, participant characteristics, data accessibility, and conflict of interest disclosures—several methodological limitations were noted. Reporting Gaps: 13 studies [ 16 , 19 , 22 , 24 – 27 , 32 , 35 , 39 , 40 , 42 , 44 ] did not report assessment methods and diagnostic criteria for exposures, outcomes, and related variables. 23 studies [ 14 , 17 , 19 , 20 , 22 – 25 , 28 – 30 , 32 , 34 – 37 , 39 – 45 ] lacked detailed descriptions of statistical methods used for instrumental variable selection. 28 studies [ 13 – 17 , 19 , 20 , 22 – 25 , 27 – 30 , 32 – 35 , 37 – 45 ] did not document procedures for handling missing data. 1 study [ 13 ] did not report sensitivity analyses or supplementary analyses. Protocol Registration: None of the included studies provided information on protocol pre-registration. Additionally, four studies [ 14 , 16 , 17 , 33 ] did not discuss the generalizability of findings across populations, exposure durations, or exposure levels.

Study description

The distribution of included studies across various outcome categories was as follows: Nervous system diseases: 5 studies [ 13 , 22 , 27 , 32 , 43 ]. Cardiovascular diseases: 7 studies [ 14 , 16 , 20 , 23 , 25 – 26 , 42 ]. Both neurological and cardiovascular diseases: 1 study [ 19 ]. Musculoskeletal system diseases: 7 studies [ 24 , 30 – 31 , 34 , 37 , 39 , 41 ]. Urogenital diseases: 4 studies [ 17 , 21 , 33 , 45 ]. Digestive system diseases: 3 studies [ 15 , 28 , 38 ]. Mental disorders: 2 studies [ 35 , 44 ]. Metabolic diseases: 2 studies [ 18 , 29 ]. Skin and connective tissue diseases: 1 study [ 36 ]. Respiratory tract diseases: 1 study [ 40 ]. In total, 93 distinct outcome variables were examined. Table  1 provides an overview of the design characteristics of the included studies.

Among the included MR studies on Hcy, only two [ 18 , 20 ] did not use genetic variations from a genome-wide association study (GWAS) that encompassed 10 European population cohorts, totaling 44,147 individuals. The average age across these cohorts ranged between 47.5 and 74.4 years, with participants’ ages spanning from 17 to 79 years [ 46 ]. A single investigation into Hcy employed genetic variants sourced from the Korean Genome and Epidemiology Study (KoGES) Consortium, encompassing a total of 8840 individuals from Korean cohorts [ 47 ]. Another study sourced Hcy data from imputed genotype data in the UK Biobank, including 57,644 individuals [ 20 ]. Outcome data for all MR studies were sourced from a large GWAS meta-analysis, along with data from the UK Biobank, FinnGen study, MEGASTROKE consortium, and potentially other similar sources. The majority of these outcome databases represent individuals of European and East Asian ancestry. For further details, See Table  1 .

Except for one study, all MR studies on Hcy reported results using the inverse-variance weighted (IVW) method as the primary approach [ 13 ]. Additionally, most studies provided detailed secondary results from the weighted median (WM) method and MR-Egger regression. A comprehensive summary of the studies included in the main MR analyses and their respective findings is available in Table  1 .

Table 1 Summary of all published Mendelian randomization (MR) estimates for the association between homocysteine (Hcy) and multiple diseases Author, Year Exposure Variable Exposure Data Source Exposure Sample Size Primary Ancestry of Exposure Outcome Variable Outcome Data Source Outcome Sample Size Primary Ancestry of Outcome Number of SNPs Main MR Analysis Method OR (95% CI) P-Value Reverse Causality Assessed (Significance) Roostaei et al, 2018 [ 13 ] Hcy GWAS meta-analysis 44,147 European AD IGAP 17,008 cases; 37,154 controls European 13 NR 1.01 (0.89, 1.15) 0.84 No (Not assessed) Larsson et al, 2019 [ 14 ] tHcy GWAS meta-analysis 44,147 European SVS MEGASTROKE consortium 16,952 cases; 404,630 noncases European 18 IVW 1.34 (1.13, 1.58)
6.7×10
− 4
No (Not assessed) WM 1.54 (1.20, 1.97)
0.001
MR-Egger 1.35 (0.81, 2.27) 0.25 LAS IVW 1.01 (0.84, 1.21) 0.89 CES IVW 0.94 (0.81, 1.07) 0.35 AIS IVW 1.09 (1.02, 1.17)
0.02
CAD IVW 1.02 (0.95, 1.09) 0.61 Wang et al, 2020 [ 15 ] PHL GWAS meta-analysis 44,147 European Gastric cancer Published GWAS 2,631 cases; 4,373 controls Chinese 15 IVW 1.09 (1.01, 1.18)
0.034
No (Not assessed) wGRS 1.07 (1.01, 1.12)
0.011
WM 1.107 (1.016, 1.207)
0.02
MR-Egger 1.089 (0.914, 1.300) 0.342 Chen et al, 2021 [ 16 ] Hcy GWAS meta-analysis 44,147 European AF GWAS meta-analysis 60,620 cases; 970,216 controls European 9 IVW 1.077 (0.993, 1.168) 0.075 No (Not assessed) WM 1.106 (0.998, 1.226) 0.054 MR-Egger 1.071 (0.856, 1.340) 0.551 He et al, 2021 [ 17 ] PHL GWAS meta-analysis 44,147 European Overall BRCA GWAS meta-analysis 133,384 cases; 113,789 controls European 15 IVW 0.97 (0.90, 1.06) 0.543 No (Not assessed) WM 0.988 (0.918, 1.064) 0.757 MR-Egger 1.115 (0.891, 1.395) 0.341 Overall PrCa 79,148 cases; 61,106 controls IVW 1.01 (0.93, 1.11) 0.774 WM 1.011 (0.916, 1.116) 0.83 MR-Egger 0.990 (0.752, 1.302) 0.941 RCC in men 3,227 cases; 4,916 controls IVW 0.99 (0.73, 1.34) 0.929 WM 0.756 (0.439, 1.302) 0.582 MR-Egger 0.402 (0.129, 1.262) 0.115 RCC in women 1,992 cases;3,095 controls IVW 0.89 (0.61, 1.31) 0.563 WM 0.891 (0.591, 1.344) 0.313 MR-Egger 0.681 (0.272, 1.707) 0.412 Lee et al, 2021 [ 18 ] Hcy KoGES Consortium 2090 cases; 3812 controls Korean MetS KoGES Consortium HEXA (676 cases; 3017 controls) and CAVAS (1052 cases; 764 controls) Korean 27 IVW 2.054 (1.649, 2.560)
< 0.001
No (Not assessed) WM 2.085 (1.730, 2.517)
< 0.001
MR-Egger 2.784 (1.478, 2.517)
0.002
5 IVW 2.061 (1.642, 2.563)
< 0.001
WM 2.083 (1.723, 2.517)
< 0.001
MR-Egger 7.950 (1.523, 41.471)
0.014
Liu et al, 2021 [ 19 ] Hcy GWAS meta-analysis 44,147 European IS (Non-subtyped) MEGASTROKE consortium 34,217 cases; 440,328 subjects European 13 IVW 1.098 (0.980, 1.229) 0.107 No (Not assessed) LAS 1.093 (0.878, 1.312) 0.424 CES 0.920 (0.785, 1.080) 0.308 SAS 1.329 (1.047, 1.612)
0.048
TIA UK Biobank 1,364 cases; 461,646 controls 1.000 (0.999, 1.001) 0.858 MS IMSGC 14,498 cases; 24,091 controls 1.154 (0.888, 1.500) 0.283 AD IGAP 21,982 cases; 41,944 controls 1.081 (0.960, 1.217) 0.198 PD IPDGC 33,674 cases; 449,056 controls 0.985 (0.853, 1.137) 0.837 ALS IALSGC 20,806 cases; 59,804 controls 1.085 (0.948, 1.241) 0.235 FTD IFLDC 515 case; 2,509 controls 1.268 (0.416, 3.863) 0.676 Miao et al, 2021 [ 20 ] Hcy UK Biobank 57,644 European CHD CARDIoGRAM and CARDIoGRAMplusC4D consortium 184,305 European 9 IVW 1.015 (0.923, 1.106) 0.752 No (Not assessed) WM 0.916 (0.789, 1.042) 0.17 AMI 171,875 IVW 1.037 (0.932, 1.142) 0.499 WM 0.967 (0.826, 1.108) 0.64 Park et al, 2021 [ 21 ] Hcy GWAS meta-analysis 44,147 European eGFR GWAS meta-analysis 567,460 European 18 IVW -
< 0.001
No (Not assessed) MR-Egger -
< 0.001
Peng et al, 2021 [ 22 ] Hcy GWAS meta-analysis 44,147 European MS IMSGC 47,429 cases; 68,374 controls European 14 IVW 0.780 (0.640, 0.940)
0.0106
No (Not assessed) WM 0.85 (0.68, 1.06) 0.141 MR-Egger 0.73 (0.46, 1.16) 0.2096 Sun et al, 2021 [ 23 ] Hcy GWAS meta-analysis 44,147 European AF GWAS meta-analysis 65 446 cases; 522 744 controls European 13 IVW 0.972 (0.919, 1.027) 0.308 No (Not assessed) WM 0.984 (0.911, 1.064) 0.694 MR-Egger 1.021(0.900, 1.158) 0.754 8 IVW 1.005(0.913, 1.106) 0.919 WM 1.050(0.926, 1.191) 0.444 MR-Egger 1.281(0.960, 1.708) 0.143 Wang et al, 2021 [ 24 ] Hcy increase GWAS meta-analysis 44,147 European FA BMD GWAS meta-analysis 10,805 European 8 IVW - 0.153 No (Not assessed) WM - 0.368 MR-Egger - 0.478 FN BMD GWAS meta-analysis 49,988 5 IVW - 0.731 WM - 0.929 MR-Egger - 0.599 LS BMD GWAS meta-analysis 44,731 5 IVW - 0.989 WM - 0.864 MR-Egger - 0.383 eBMD UK Biobank 426,824 5 IVW - 0.468 WM - 0.864 MR-Egger - 0.383 Bone fracture UK Biobank 426,795 5 IVW - 0.562 WM - 0.475 MR-Egger - 0.784 Hcy decrease GWAS meta-analysis 44,147 European FA BMD GWAS meta-analysis 10,805 6 IVW -
0.0007
WM -
0.041
MR-Egger - 0.236 FN BMD GWAS meta-analysis 49,988 6 IVW - 0.582 WM - 0.703 MR-Egger - 0.421 LS BMD GWAS meta-analysis 44,731 6 IVW - 0.572 WM - 0.912 MR-Egger - 0.169 eBMD UK Biobank 426,824 6 IVW - 0.328 WM - 0.053 MR-Egger - 0.988 Bone fracture UK Biobank 426,795 6 IVW - 0.544 WM - 0.909 MR-Egger - 0.882 Xu et al, 2021 [ 25 ] Hcy GWAS meta-analysis 44,147 European CAD Published GWAS 3,968 cases; 11,696 controls European 9 IVW 1.14 (0.82, 1.58) 0.43 No (Not assessed) WM 1.46 (0.71, 3.00) 0.33 MR-Egger 1.70 (0.69, 4.24) 0.25 MR-PRESSO 1.14 (0.84, 1.55) 0.43 Yuan et al, 2021 [ 26 ] tHcy GWAS meta-analysis 44,147 European AA UK Biobank and FinnGen UK Biobank (2,261 cases; 365,300 controls) and FinnGen (1,919 cases; 167,843 controls) European 14 IVW 1.11 (0.92, 1.35) 0.286 No (Not assessed) AF Consortium and FinnGen Consortium (60,620 cases; 970,216 controls) and FinnGen (17,325 cases; 97,214 controls) European 0.96 (0.91, 1.01) 0.098 AVS UK Biobank UK Biobank (3,528 cases; 364,033 controls) European 1.14 (0.85, 1.5) 0.356 CAD CARDIoGRAMplusC4D + UKBB 122,733 cases; 424,528 controls Mixed 1.05 (0.96, 1.15) 0.098 HF HERMES consortium and FinnGen HERMES consortium (47,309 cases; 930,014 controls)and FinnGen (9,576 cases; 159,286 controls) European 0.96 (0.88, 1.05) 0.372 Stroke MEGASTROKE consortium、UK Biobank and FinnGen MEGASTROKE consortium (40,585 cases; 406,111 controls)、UK Biobank (12,036 cases; 355,525 controls) and FinnGen (14,171 cases; 133,027controls) European 1.11 (1.03, 1.20)
0.008
IH ISGC and FinnGen ISGC (3,223 cases; 3,725 controls) and FinnGen (1,504 cases; 366,057 controls) European 1.09 (0.89, 1.34) 0.411 SH consortium and FinnGen consortium (7,495 cases; 71,934 controls) and FinnGen (1,019 cases; 163,508 controls) European 1.26 (1.05, 1.51)
0.013
IS MEGASTROKE consortium、UK Biobank and FinnGen MEGASTROKE consortium (34,217)、UK Biobank (6,566 cases; 360,995 controls) and FinnGen (8,046 cases; 164,286 controls) European 1.11 (1.03, 1.21)
0.011
TIA UK Biobank and FinnGen UK Biobank (4,813 cases; 362,748 controls) and FinnGen (6,729 cases; 164,286 controls) European 1.15 (0.99, 1.16) 0.066 VT UK Biobank and FinnGen UK Biobank (16,412 cases; 351,149 controls) and FinnGen (6,913 cases; 169,986 controls) European 1.05 (0.94, 1.16) 0.392 PAD UK Biobank and FinnGen UK Biobank (4,593 cases; 362,968 controls) and FinnGen (5,323 cases; 167,843 controls) European 1.06 (0.91, 1.23) 0.486 Zhao et al, 2021 [ 27 ] tHcy GWAS meta-analysis 44,147 European PD risk GWAS meta-analysis 33,674 cases; 449,056 controls European 14 IVW 1.010 (0.880, 1.160) 0.868 No (Not assessed) WM 1.03 (0.87, 1.23) 0.715 MR-Egger 1.22 (0.90, 1.64) 0.199 MR-PRESSO 1.01 (0.92, 1.11) 0.815 Age at onset of PD IPDGC GWAS 17,996 cases IVW 0.522 (0.183, 1.492) 0.222 WM -0.32 (-1.56, 0.92) 0.715 MR-Egger -0.33 (-2.74, 2.08) 0.788 MR-PRESSO -0.65 (-1.70, 0.40) 0.244 Chen et al, 2022 [ 28 ] Hcy GWAS meta-analysis 44,147 European NAFLD GWAS meta-analysis 1,578 cases; 307576 controls European 12 IVW 1.264 (0.924, 1.728) 0.143 No (Not assessed) WM 1.231 (0.973, 2.203) 0.068 MR-Egger 1.398 (0.807, 3.001) 0.187 NASH 99 cases; 309055 controls IVW 1.891 (0.509, 7.022) 0.341 WM 2.321 (0.261, 7.092) 0.714 MR-Egger 4.332 (0.07, 21.977) 0.882 Cirrhosis 826 cases; 306145 controls IVW 0.811 (0.498, 1.322) 0.401 WM 1.384 (0.361, 1.293) 0.242 MR-Egger 1.605 (0.149, 0.952)
0.039
Cheng et al, 2022 [ 29 ] Hcy GWAS meta-analysis 44,147 European T2DM GWAS meta-analysis 74,124 cases; 824,006 controls European 14 IVW 1.08 (0.95, 1.21) 0.249 No (Not assessed) WM 1.148 (1.023, 1.289)
0.019
MR-Egger 1.071 (0.791, 1.452) 0.666 Fu et al, 2022 [ 30 ] Hcy GWAS meta-analysis 44,147 European Musculoskeletal system diseases FinnGen 218,792 European 13 IVW 1.074 (0.994, 1.159) 0.07 No (Not assessed) WM 1.057 (0.973, 1.148) 0.187 MR-Egger 1.121 (0.940, 1.337) 0.205 Soft tissue disorders 13 IVW 1.069 (1.001, 1.141)
0.045
WM 1.069 (0.982, 1.163) 0.122 MR-Egger 1.109 (0.962, 1.277) 0.155 Knee OA UK Biobank 455,221 14 IVW 1.119 (1.032, 1.214)
0.007
WM 1.078 (0.977, 1.189) 0.134 MR-Egger 1.122 (0.906, 1.390) 0.291 Hip OA 14 IVW 1.066 (0.942, 1.206) 0.311 WM 1.038 (0.903, 1.193) 0.603 MR-Egger 1.128 (0.842, 1.513) 0.419 Hospital-diagnosed OA UK Biobank 327,918 14 IVW 1.178 (1.012, 1.370)
0.034
WM 1.206 (0.985, 1.476) 0.069 MR-Egger 1.312 (0.935, 1.842) 0.117 Osteoporosis with pathological fracture FinnGen 173,619 13 IVW 1.597 (1.036, 2.460)
0.034
WM 1.673 (0.889, 3.149) 0.11 MR-Egger 2.110 (0.824, 5.404) 0.12 Body fat percentage UK Biobank 331,117 14 IVW - 0.703 WM - 0.715 MR-Egger - 0.504 Trunk fat percentage 14 IVW - 0.721 WM - 0.125 MR-Egger - 0.521 Left arm fat percentage 14 IVW - 0.46 WM - 0.216 MR-Egger - 0.491 Right arm fat percentage 14 IVW - 0.609 WM - 0.275 MR-Egger - 0.328 Left leg fat percentage 14 IVW - 0.963 WM - 0.624 MR-Egger - 0.432 Right leg fat percentage 14 IVW - 0.871 WM - 0.51 MR-Egger - 0.548 Pediatric BMD Published GWAS 8327 13 IVW - 0.693 WM - 0.877 MR-Egger - 0.144 Lean body mass 13 IVW - 0.82 WM - 0.185 MR-Egger - 0.204 Whole mass GEFOS 38292 13 IVW - 0.183 WM - 0.076 MR-Egger -
0.021
Append mass 13 IVW - 0.176 WM -
0.003
MR-Egger -
0.008
Fu et al, 2022 [ 31 ] Hcy GWAS meta-analysis 44,147 European FA BMD GEFOS Consortium 8,143 European 11 IVW - 0.545 No (Not assessed) WM - 0.59 MR-Egger - 0.403 FN BMD GEFOS Consortium 32,735 9 IVW - 0.163 WM - 0.621 MR-Egger - 0.382 LS BMD GEFOS Consortium 28,498 9 IVW - 0.297 WM - 0.209 MR-Egger - 0.391 Heel BMD UK Biobank 142,487 11 IVW -
9.59E-04
WM -
0.013
MR-Egger - 0.268 Total body BMD GEFOS Consortium 66,628 11 IVW - 0.211 WM - 0.22 MR-Egger - 0.137 Total body BMD of age 0–15 GEFOS Consortium 11,807 11 IVW - 0.779 WM - 0.418 MR-Egger - 0.142 Total body BMD of age 15–30 GEFOS Consortium 4,180 11 IVW - 0.741 WM - 0.905 MR-Egger - 0.99 Total body BMD of age 30–45 GEFOS Consortium 10,062 11 IVW - 0.707 WM - 0.535 MR-Egger - 0.108 Total body BMD of age 45–60 GEFOS Consortium 18,805 11 IVW - 0.472 WM - 0.526 MR-Egger - 0.512 Total body BMD of age over 60 GEFOS Consortium 22,504 11 IVW - 0.342 WM - 0.276 MR-Egger - 0.383 Ma et al, 2022 [ 32 ] Hcy GWAS meta-analysis 44,147 European IA Published GWAS 7,495 cases; 71,934 controls European 9 IVW 1.124 (0.923, 1.368) 0.246 No (Not assessed) WM 1.204 (0.932, 1.555) 0.155 MR-Egger 1.236 (0.818, 1.869) 0.348 SAH 2,070 cases; 71,934 controls 9 IVW 1.104 (0.878, 1.387) 0.398 WM 1.239 (0.927, 1.657) 0.148 MR-Egger 1.291 (0.799, 2.085) 0.332 UIA 5,140 cases; 71,934 controls 7 IVW 1.126 (0.682, 1.858) 0.644 WM 1.091 (0.604, 1.969) 0.774 MR-Egger 1.103 (0.311, 3.913) 0.885 Xiong et al, 2022 [ 33 ] tHcy GWAS meta-analysis 44,147 European CKD CKDGen consortium and PAGE CKDGen consortium (41,395 cases; 439,303 controls)and PAGE (49,839) European 14 IVW 1.24 (1.07, 1.44)
< 0.05
No (Not assessed) eGFR IVW -
< 0.01
WM -
< 0.001
MR-Egger -
0.049
eGFR (Excluding diabetes patients) IVW -
0.008
WM -
0.002
MR-Egger - 0.076 Yu et al, 2022 [ 34 ] Hcy increase GWAS meta-analysis 44,147 European Grip strength (right) UK Biobank 461,089 European 7 IVW -
5.53×10
− 4
No (Not assessed) WM -
6.02E–03
MR-Egger - 0.69 Grip strength (left) 461,026 7 IVW -
1.45×10
− 5
WM -
6.80E–04
MR-Egger - 0.579 Walking pace 335,349 7 IVW -
3.18×10
− 4
WM -
5.66E–03
MR-Egger - 0.0747 ALM 450,243 7 IVW -
1.03×10
− 5
WM -
1.01E–03
MR-Egger - 0.226 Hcy decrease GWAS meta-analysis 44,147 European Grip strength (right) UK Biobank 461,089 European 4 IVW - 0.82 WM - 0.42 MR-Egger - 0.93 Grip strength (left) 461,026 3 IVW - 0.64 WM - 0.81 MR-Egger - 0.43 Walking pace 335,349 5 IVW - 0.61 WM - 0.39 MR-Egger - 0.67 ALM 450,243 4 IVW - 0.06 WM - 0.14 MR-Egger - 0.99 Yu et al, 2022 [ 35 ] Hcy GWAS meta-analysis 44,147 European SCZ GWAS meta-analysis 67,390 cases; 94,015 controls European 10 IVW 1.110 (1.028, 1.198)
2.74× 10
− 3
No (Not assessed) GSMR 1.115(1.041, 1.194)
1.73E-03
MDD Published GWAS 16,823 cases; 25,632 controls 13 IVW 0.948 (0.890, 1.009) 0.115 GSMR 0.951 (0.890, 1.017) 0.139 BD GWAS meta-analysis 41,917 cases; 371,549 controls 11 IVW 1.081 (0.998, 1.171) 0.054 GSMR 1.088 (1.006, 1.177)
0.037
BD-I GWAS meta-analysis 25,060 cases; 449,978 controls 13 IVW 1.133 (1.031, 1.245)
9.44×10
− 3
GSMR 1.144 (1.041, 1.257)
5.23E-03
BD-II GWAS meta-analysis 6,781 cases; 364,075 controls 13 IVW 0.977 (0.832, 1.147) 0.773 GSMR 0.977 (0.832, 1.147) 0.783 Chen et al, 2023 [ 36 ] Hcy GWAS meta-analysis 44,147 European Psoriasis FinnGen consortium 9,267 cases; 364,071 controls European 11 IVW 0.995 (0.863, 1.146) 0.941 No (Not assessed) WM 0.985 (0.834, 1.164) 0.862 MR-Egger 0.959 (0.704, 1.305) 0.795 Fu et al, 2023 [ 37 ] Hcy GWAS meta-analysis 44,147 European Birth weight Published GWAS 133,903 European 9 IVW - 0.06 Yes (p = 0.666) Childhood BMl 39,620 - 0.627 Yes (p = 0.607) WC adjusted for BMl 231,353 - 0.349 Yes (p = 0.473) WHR adjusted for BMI 210,082 -
0.03
Yes (p = 0.542) BMI 454,884 - 0.368 Yes (p = 0.01) BFFM 454,850 - 0.105 Yes (p = 0.57) BFM 454,137 - 0.221 Yes (p = 0.659) BFP 454,633 - 0.095 Yes (p = 0.592) Fu et al, 2023 [ 38 ] Hcy GWAS meta-analysis 44,147 European NAFLD Two meta-analyses of GWAS 8,434 cases; 770,180 controls European 9 IVW 1.21 (1.01, 1.43)
0.041
Yes (p = 0.156) (Ghodsian et al GWAS) WM 1.20 (0.97, 1.43) 0.067 NAFLD 1,483 cases; 17,781 controls IVW 1.52 (1.01, 2.13)
0.048
(Anstee et al GWAS) WM 1.50 (0.66, 2.33) 0.189 ALP UK Biobank 344,292 IVW -
0.039
No (Not assessed) WM - 0.074 MR-PRESSO - 0.071 ALT 344,136 IVW -
0.007
WM -
0.002
MR-PRESSO -
0.031
AST 342,990 IVW -
0.018
WM -
0.026
MR-PRESSO - 0.064 Hong et al, 2023 [ 39 ] Hcy GWAS meta-analysis 44,147 European Overall OA Published GWAS 177,517 cases; 649,173 controls European and East Asian 11 IVW 1.098 (1.044, 1.155)
< 0.001
No (Not assessed) WM 1.074 (1.000, 1.154)
0.05
MR-Egger 1.120 (0.941, 1.333) 0.233 Knee OA NR NR IVW 1.080 (1.000, 1.167)
0.05
WM 1.088 (0.979, 1.208) 0.118 MR-Egger 1.191 (0.917, 1.546) 0.223 Hip OA IVW 1.171 (1.057, 1.297)
0.002
WM 1.155 (1.001, 1.334)
0.049
MR-Egger 1.395 (0.952, 2.044) 0.126 Spine OA IVW 1.112 (0.995, 1.243) 0.062 WM 1.071 (0.921, 1.244) 0.374 MR-Egger 1.210 (0.868, 1.686) 0.289 Hand OA IVW 1.040 (0.907, 1.193) 0.574 WM 1.071 (0.884, 1.299) 0.483 MR-Egger 0.856 (0.506, 1.450) 0.578 Thumb OA IVW 1.057 (0.874, 1.278) 0.571 WM 1.083 (0.840, 1.395) 0.54 MR-Egger 0.836 (0.456, 1.532) 0.576 Hu et al, 2023 [ 40 ] Hcy GWAS meta-analysis 44,147 European COPD hospital admissions IEU Open GWAS 6,500 cases; 212,292 controls European 14 IVW 1.06 (0.91, 1.24) 0.42 No (Not assessed) WM 1.08 (0.88–1.33) 0.44 MR-Egger 1.10 (0.79–1.53) 0.57 Asthma/COPD 21,444 cases; 186,723 controls IVW 0.97 (089, 1.06) 0.55 WM 1.01 (0.89–1.15) 0.84 MR-Egger 1.09 (0.90–1.33) 0.4 COPD-related chronic (opportunistic) infections 234 cases; 186,723 controls IVW 1.50 (0.57, 3.99) 0.42 WM 2.32 (0.57–9.48) 0.24 MR-Egger 0.09 (0.05–1.54) 0.12 COPD/asthma/ILD-related pneumonia or pneumonia-derived septicemia 27,715 cases; 159,867 controls IVW 0.93 (0.86, 1.02) 0.13 WM 1.02 (0.91–1.14) 0.71 MR-Egger 1.07 (0.89–1.28) 0.47 COPD-related respiratory insufficiency 1,031 cases; 186,723 controls IVW 1.00 (0.70, 1.44) 0.99 WM 1.01 (0.62–1.67) 0.96 MR-Egger 1.28 (0.59–2.81) 0.54 Wang et al, 2023 [ 41 ] Hcy GWAS meta-analysis 44,147 European FA BMD GEFOS UK Biobank 8,143 European 8 IVW 0.957 (0.771, 1.188) 0.69 No (Not assessed) WM 0.942 (0.779, 1.139) 0.537 MR-Egger 1.084 (0.680, 1.729) 0.746 Lumbar BMD 28,498 7 IVW 0.856 (0.720, 1.016) 0.077 WM 0.844 (0.711, 1.001) 0.051 MR-Egger 0.635 (0.317, 1.274) 0.256 Heel BMD 142,487 8 IVW 0.960 (0.927, 0.990)
0.011
WM 0.967 (0.929, 1.005) 0.084 MR-Egger 0.981 (0.918, 1.049) 0.607 Wang et al, 2023 [ 42 ] Hcy GWAS meta-analysis 44,147 European Congestive heart failure Published GWAS 897 cases; 455,451 controls European 3 IVW 1.753 (0.674, 4.562) 0.25 No (Not assessed) WM 1.849 (1.014, 3.372)
0.045
MR-Egger 5.472(1.797, 16.665) 0.205 Cardiomyopathy FinnGen study 3100 cases; 156,711 controls 12 IVW 0.805 (0.583, 1.112) 0.189 WM 0.829(0.596, 1.154) 0.267 MR-Egger 1.126(0.576, 2.199) 0.736 Non-ischemic cardiomyopathy FinnGen study 11,400 cases; 1.751.752 controls 12 IVW 1.064 (0.927, 1.222) 0.379 WM 1.004 (0.845, 1.194) 0.961 MR-Egger 1.006(0.744, 1.361) 0.97 Gao et al, 2024 [ 43 ] Hcy GWAS meta-analysis 44,147 European GMV UK Biobank imaging database 7,916 European and White British 9 IVW 0.976 (0.871, 1.094) 0.068 No (Not assessed) WM 1.068 (0.938, 1.214) 0.324 MR-Egger 1.103 (0.895, 1.360) 0.388 8 IVW 0.858 (0.738, 0.999)
0.048
WM 0.836 (0.684, 1.021) 0.076 MR-Egger 0.725 (0.446, 1.178) 0.242 BV 9 IVW 0.958 (0.808, 1.135) 0.621 WM 1.078 (0.928, 1.252) 0.323 MR-Egger 1.113 (0.805, 1.540) 0.537 8 IVW 0.808 (0.652, 1.000)
0.049
WM 0.845 (0.651, 1.096) 0.202 MR-Egger 0.607 (0.301, 1.222) 0.211 Jin et al, 2024 [ 44 ] Hcy GWAS meta-analysis 44,147 European ASD iPSYCH-PGC 18,382 cases; 27,969 controls European 13 IVW 1.03 (0.92, 1.15) 0.63 No (Not assessed) WM 1.02 (0.88, 1.18) 0.84 MR-Egger 1.04 (0.82, 1.33) 0.74 Lin et al, 2024 [ 45 ] Hcy GWAS meta-analysis 44,147 European PCOS FinnGen GWAS 994; 165,817 controls European 14 IVW 1.163 (0.705, 1.919) 0.556 No (Not assessed) Tyrmi et al GWAS 3,609; 229,788 controls 0.988 (0.814, 1.200) 0.906 Day et al 4,138; 20,129 controls 1.903 (0.817, 1.464) 0.548 Abbreviations : OR, odds ratio; CI, confidential interval; NR, not reported; IVW, inverse variance weighted; WM, weighted median; wGRS, weighted genetic risk score; GSMR, Generalized Summary-data based Mendelian Randomization; Hcy, homocysteine; CAD, coronary artery disease; MI, myocardial infarction; AD, Alzheimer’s disease; IGAP, International Genomics of Alzheimer’s Project; tHcy, total homocysteine; SVS, small vessel stroke; LAS, large artery atherosclerosis stroke; CES, cardioembolism stroke; SAS, small artery occlusion stroke; AIS, all ischemic stroke; PHL, plasma homocysteine level; AF, atrial fibrillation; BRCA, breast cancer; PrCa, prostate cancer; RCC, renal cell carcinoma; MetS, metabolic syndrome; IS, ischemic stroke; IH, Intracerebral hemorrhage; SH, Subarachnoid hemorrhage; AA, Aortic aneurysm; AVS, Aortic valve stenosis; TIA, transient ischemic attack; VT, Venous thromboembolism; PVD, Peripheral vessel disease; ISGC, International Stroke Genetic Consortium; MS, multiple sclerosis; PD, Parkinson’s disease; ALS, amyotrophic lateral sclerosis; FTD, frontotemporal dementia; IMSGC, International Multiple Sclerosis Genetics Consortium; IPDGC, International Parkinson’s Disease Genomics Consortium; IALSGC, International Amyotrophic Lateral Sclerosis Genomics Consortium; IFLDC, International Frontotemporal Lobar Degeneration Collaboration; CHD, coronary heart disease; AMI, acute myocardial infarction; CARDIoGRAM, Coronary ARtery DIsease Genome wide Replication and Meta-analysis; C4D, Coronary Artery Disease; BMD, bone mineral density; FA: forearm; FN, femoral neck; LS, lumbar spine; eBMD, estimated heel BMD; GEFO, Genetic Factors for Osteoporosis Consortium; CAD, coronary artery disease; IA, intracranial aneurysm; SAH, subarachnoid hemorrhage; UIA, unruptured intracranial aneurysm; eGFR, estimated glomerular filtration rate; PAGE, Population Architecture using Genomics and Epidemiology; CKD, chronic kidney disease; ALM, appendicular lean mass; SCZ, schizophrenia; BD, bipolar disorder; MDD, major depressive disorder; NAFLD, nonalcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; T2DM, type 2 diabetes mellitus; BMI, body mass index; WHR, waist-to-hip ratio; WC, waist circumference; BFFM, body fat-free mass; BFP, body fat percentage; BFM, body fat mass; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; OA, osteoarthritis; COPD, chronic obstructive pulmonary disease; ILD, interstitial lung disease; OP, osteoporosis; BV, brain volume; GMV, gray matter volume; ASD, autism spectrum disorder; UKB, UK biobank; PCOS, Polycystic ovary syndrome

Table 1 Summary of all published Mendelian randomization (MR) estimates for the association between homocysteine (Hcy) and multiple diseases Author, Year Exposure Variable Exposure Data Source Exposure Sample Size Primary Ancestry of Exposure Outcome Variable Outcome Data Source Outcome Sample Size Primary Ancestry of Outcome Number of SNPs Main MR Analysis Method OR (95% CI) P-Value Reverse Causality Assessed (Significance) Roostaei et al, 2018 [ 13 ] Hcy GWAS meta-analysis 44,147 European AD IGAP 17,008 cases; 37,154 controls European 13 NR 1.01 (0.89, 1.15) 0.84 No (Not assessed) Larsson et al, 2019 [ 14 ] tHcy GWAS meta-analysis 44,147 European SVS MEGASTROKE consortium 16,952 cases; 404,630 noncases European 18 IVW 1.34 (1.13, 1.58)
6.7×10
− 4
No (Not assessed) WM 1.54 (1.20, 1.97)
0.001
MR-Egger 1.35 (0.81, 2.27) 0.25 LAS IVW 1.01 (0.84, 1.21) 0.89 CES IVW 0.94 (0.81, 1.07) 0.35 AIS IVW 1.09 (1.02, 1.17)
0.02
CAD IVW 1.02 (0.95, 1.09) 0.61 Wang et al, 2020 [ 15 ] PHL GWAS meta-analysis 44,147 European Gastric cancer Published GWAS 2,631 cases; 4,373 controls Chinese 15 IVW 1.09 (1.01, 1.18)
0.034
No (Not assessed) wGRS 1.07 (1.01, 1.12)
0.011
WM 1.107 (1.016, 1.207)
0.02
MR-Egger 1.089 (0.914, 1.300) 0.342 Chen et al, 2021 [ 16 ] Hcy GWAS meta-analysis 44,147 European AF GWAS meta-analysis 60,620 cases; 970,216 controls European 9 IVW 1.077 (0.993, 1.168) 0.075 No (Not assessed) WM 1.106 (0.998, 1.226) 0.054 MR-Egger 1.071 (0.856, 1.340) 0.551 He et al, 2021 [ 17 ] PHL GWAS meta-analysis 44,147 European Overall BRCA GWAS meta-analysis 133,384 cases; 113,789 controls European 15 IVW 0.97 (0.90, 1.06) 0.543 No (Not assessed) WM 0.988 (0.918, 1.064) 0.757 MR-Egger 1.115 (0.891, 1.395) 0.341 Overall PrCa 79,148 cases; 61,106 controls IVW 1.01 (0.93, 1.11) 0.774 WM 1.011 (0.916, 1.116) 0.83 MR-Egger 0.990 (0.752, 1.302) 0.941 RCC in men 3,227 cases; 4,916 controls IVW 0.99 (0.73, 1.34) 0.929 WM 0.756 (0.439, 1.302) 0.582 MR-Egger 0.402 (0.129, 1.262) 0.115 RCC in women 1,992 cases;3,095 controls IVW 0.89 (0.61, 1.31) 0.563 WM 0.891 (0.591, 1.344) 0.313 MR-Egger 0.681 (0.272, 1.707) 0.412 Lee et al, 2021 [ 18 ] Hcy KoGES Consortium 2090 cases; 3812 controls Korean MetS KoGES Consortium HEXA (676 cases; 3017 controls) and CAVAS (1052 cases; 764 controls) Korean 27 IVW 2.054 (1.649, 2.560)
< 0.001
No (Not assessed) WM 2.085 (1.730, 2.517)
< 0.001
MR-Egger 2.784 (1.478, 2.517)
0.002
5 IVW 2.061 (1.642, 2.563)
< 0.001
WM 2.083 (1.723, 2.517)
< 0.001
MR-Egger 7.950 (1.523, 41.471)
0.014
Liu et al, 2021 [ 19 ] Hcy GWAS meta-analysis 44,147 European IS (Non-subtyped) MEGASTROKE consortium 34,217 cases; 440,328 subjects European 13 IVW 1.098 (0.980, 1.229) 0.107 No (Not assessed) LAS 1.093 (0.878, 1.312) 0.424 CES 0.920 (0.785, 1.080) 0.308 SAS 1.329 (1.047, 1.612)
0.048
TIA UK Biobank 1,364 cases; 461,646 controls 1.000 (0.999, 1.001) 0.858 MS IMSGC 14,498 cases; 24,091 controls 1.154 (0.888, 1.500) 0.283 AD IGAP 21,982 cases; 41,944 controls 1.081 (0.960, 1.217) 0.198 PD IPDGC 33,674 cases; 449,056 controls 0.985 (0.853, 1.137) 0.837 ALS IALSGC 20,806 cases; 59,804 controls 1.085 (0.948, 1.241) 0.235 FTD IFLDC 515 case; 2,509 controls 1.268 (0.416, 3.863) 0.676 Miao et al, 2021 [ 20 ] Hcy UK Biobank 57,644 European CHD CARDIoGRAM and CARDIoGRAMplusC4D consortium 184,305 European 9 IVW 1.015 (0.923, 1.106) 0.752 No (Not assessed) WM 0.916 (0.789, 1.042) 0.17 AMI 171,875 IVW 1.037 (0.932, 1.142) 0.499 WM 0.967 (0.826, 1.108) 0.64 Park et al, 2021 [ 21 ] Hcy GWAS meta-analysis 44,147 European eGFR GWAS meta-analysis 567,460 European 18 IVW -
< 0.001
No (Not assessed) MR-Egger -
< 0.001
Peng et al, 2021 [ 22 ] Hcy GWAS meta-analysis 44,147 European MS IMSGC 47,429 cases; 68,374 controls European 14 IVW 0.780 (0.640, 0.940)
0.0106
No (Not assessed) WM 0.85 (0.68, 1.06) 0.141 MR-Egger 0.73 (0.46, 1.16) 0.2096 Sun et al, 2021 [ 23 ] Hcy GWAS meta-analysis 44,147 European AF GWAS meta-analysis 65 446 cases; 522 744 controls European 13 IVW 0.972 (0.919, 1.027) 0.308 No (Not assessed) WM 0.984 (0.911, 1.064) 0.694 MR-Egger 1.021(0.900, 1.158) 0.754 8 IVW 1.005(0.913, 1.106) 0.919 WM 1.050(0.926, 1.191) 0.444 MR-Egger 1.281(0.960, 1.708) 0.143 Wang et al, 2021 [ 24 ] Hcy increase GWAS meta-analysis 44,147 European FA BMD GWAS meta-analysis 10,805 European 8 IVW - 0.153 No (Not assessed) WM - 0.368 MR-Egger - 0.478 FN BMD GWAS meta-analysis 49,988 5 IVW - 0.731 WM - 0.929 MR-Egger - 0.599 LS BMD GWAS meta-analysis 44,731 5 IVW - 0.989 WM - 0.864 MR-Egger - 0.383 eBMD UK Biobank 426,824 5 IVW - 0.468 WM - 0.864 MR-Egger - 0.383 Bone fracture UK Biobank 426,795 5 IVW - 0.562 WM - 0.475 MR-Egger - 0.784 Hcy decrease GWAS meta-analysis 44,147 European FA BMD GWAS meta-analysis 10,805 6 IVW -
0.0007
WM -
0.041
MR-Egger - 0.236 FN BMD GWAS meta-analysis 49,988 6 IVW - 0.582 WM - 0.703 MR-Egger - 0.421 LS BMD GWAS meta-analysis 44,731 6 IVW - 0.572 WM - 0.912 MR-Egger - 0.169 eBMD UK Biobank 426,824 6 IVW - 0.328 WM - 0.053 MR-Egger - 0.988 Bone fracture UK Biobank 426,795 6 IVW - 0.544 WM - 0.909 MR-Egger - 0.882 Xu et al, 2021 [ 25 ] Hcy GWAS meta-analysis 44,147 European CAD Published GWAS 3,968 cases; 11,696 controls European 9 IVW 1.14 (0.82, 1.58) 0.43 No (Not assessed) WM 1.46 (0.71, 3.00) 0.33 MR-Egger 1.70 (0.69, 4.24) 0.25 MR-PRESSO 1.14 (0.84, 1.55) 0.43 Yuan et al, 2021 [ 26 ] tHcy GWAS meta-analysis 44,147 European AA UK Biobank and FinnGen UK Biobank (2,261 cases; 365,300 controls) and FinnGen (1,919 cases; 167,843 controls) European 14 IVW 1.11 (0.92, 1.35) 0.286 No (Not assessed) AF Consortium and FinnGen Consortium (60,620 cases; 970,216 controls) and FinnGen (17,325 cases; 97,214 controls) European 0.96 (0.91, 1.01) 0.098 AVS UK Biobank UK Biobank (3,528 cases; 364,033 controls) European 1.14 (0.85, 1.5) 0.356 CAD CARDIoGRAMplusC4D + UKBB 122,733 cases; 424,528 controls Mixed 1.05 (0.96, 1.15) 0.098 HF HERMES consortium and FinnGen HERMES consortium (47,309 cases; 930,014 controls)and FinnGen (9,576 cases; 159,286 controls) European 0.96 (0.88, 1.05) 0.372 Stroke MEGASTROKE consortium、UK Biobank and FinnGen MEGASTROKE consortium (40,585 cases; 406,111 controls)、UK Biobank (12,036 cases; 355,525 controls) and FinnGen (14,171 cases; 133,027controls) European 1.11 (1.03, 1.20)
0.008
IH ISGC and FinnGen ISGC (3,223 cases; 3,725 controls) and FinnGen (1,504 cases; 366,057 controls) European 1.09 (0.89, 1.34) 0.411 SH consortium and FinnGen consortium (7,495 cases; 71,934 controls) and FinnGen (1,019 cases; 163,508 controls) European 1.26 (1.05, 1.51)
0.013
IS MEGASTROKE consortium、UK Biobank and FinnGen MEGASTROKE consortium (34,217)、UK Biobank (6,566 cases; 360,995 controls) and FinnGen (8,046 cases; 164,286 controls) European 1.11 (1.03, 1.21)
0.011
TIA UK Biobank and FinnGen UK Biobank (4,813 cases; 362,748 controls) and FinnGen (6,729 cases; 164,286 controls) European 1.15 (0.99, 1.16) 0.066 VT UK Biobank and FinnGen UK Biobank (16,412 cases; 351,149 controls) and FinnGen (6,913 cases; 169,986 controls) European 1.05 (0.94, 1.16) 0.392 PAD UK Biobank and FinnGen UK Biobank (4,593 cases; 362,968 controls) and FinnGen (5,323 cases; 167,843 controls) European 1.06 (0.91, 1.23) 0.486 Zhao et al, 2021 [ 27 ] tHcy GWAS meta-analysis 44,147 European PD risk GWAS meta-analysis 33,674 cases; 449,056 controls European 14 IVW 1.010 (0.880, 1.160) 0.868 No (Not assessed) WM 1.03 (0.87, 1.23) 0.715 MR-Egger 1.22 (0.90, 1.64) 0.199 MR-PRESSO 1.01 (0.92, 1.11) 0.815 Age at onset of PD IPDGC GWAS 17,996 cases IVW 0.522 (0.183, 1.492) 0.222 WM -0.32 (-1.56, 0.92) 0.715 MR-Egger -0.33 (-2.74, 2.08) 0.788 MR-PRESSO -0.65 (-1.70, 0.40) 0.244 Chen et al, 2022 [ 28 ] Hcy GWAS meta-analysis 44,147 European NAFLD GWAS meta-analysis 1,578 cases; 307576 controls European 12 IVW 1.264 (0.924, 1.728) 0.143 No (Not assessed) WM 1.231 (0.973, 2.203) 0.068 MR-Egger 1.398 (0.807, 3.001) 0.187 NASH 99 cases; 309055 controls IVW 1.891 (0.509, 7.022) 0.341 WM 2.321 (0.261, 7.092) 0.714 MR-Egger 4.332 (0.07, 21.977) 0.882 Cirrhosis 826 cases; 306145 controls IVW 0.811 (0.498, 1.322) 0.401 WM 1.384 (0.361, 1.293) 0.242 MR-Egger 1.605 (0.149, 0.952)
0.039
Cheng et al, 2022 [ 29 ] Hcy GWAS meta-analysis 44,147 European T2DM GWAS meta-analysis 74,124 cases; 824,006 controls European 14 IVW 1.08 (0.95, 1.21) 0.249 No (Not assessed) WM 1.148 (1.023, 1.289)
0.019
MR-Egger 1.071 (0.791, 1.452) 0.666 Fu et al, 2022 [ 30 ] Hcy GWAS meta-analysis 44,147 European Musculoskeletal system diseases FinnGen 218,792 European 13 IVW 1.074 (0.994, 1.159) 0.07 No (Not assessed) WM 1.057 (0.973, 1.148) 0.187 MR-Egger 1.121 (0.940, 1.337) 0.205 Soft tissue disorders 13 IVW 1.069 (1.001, 1.141)
0.045
WM 1.069 (0.982, 1.163) 0.122 MR-Egger 1.109 (0.962, 1.277) 0.155 Knee OA UK Biobank 455,221 14 IVW 1.119 (1.032, 1.214)
0.007
WM 1.078 (0.977, 1.189) 0.134 MR-Egger 1.122 (0.906, 1.390) 0.291 Hip OA 14 IVW 1.066 (0.942, 1.206) 0.311 WM 1.038 (0.903, 1.193) 0.603 MR-Egger 1.128 (0.842, 1.513) 0.419 Hospital-diagnosed OA UK Biobank 327,918 14 IVW 1.178 (1.012, 1.370)
0.034
WM 1.206 (0.985, 1.476) 0.069 MR-Egger 1.312 (0.935, 1.842) 0.117 Osteoporosis with pathological fracture FinnGen 173,619 13 IVW 1.597 (1.036, 2.460)
0.034
WM 1.673 (0.889, 3.149) 0.11 MR-Egger 2.110 (0.824, 5.404) 0.12 Body fat percentage UK Biobank 331,117 14 IVW - 0.703 WM - 0.715 MR-Egger - 0.504 Trunk fat percentage 14 IVW - 0.721 WM - 0.125 MR-Egger - 0.521 Left arm fat percentage 14 IVW - 0.46 WM - 0.216 MR-Egger - 0.491 Right arm fat percentage 14 IVW - 0.609 WM - 0.275 MR-Egger - 0.328 Left leg fat percentage 14 IVW - 0.963 WM - 0.624 MR-Egger - 0.432 Right leg fat percentage 14 IVW - 0.871 WM - 0.51 MR-Egger - 0.548 Pediatric BMD Published GWAS 8327 13 IVW - 0.693 WM - 0.877 MR-Egger - 0.144 Lean body mass 13 IVW - 0.82 WM - 0.185 MR-Egger - 0.204 Whole mass GEFOS 38292 13 IVW - 0.183 WM - 0.076 MR-Egger -
0.021
Append mass 13 IVW - 0.176 WM -
0.003
MR-Egger -
0.008
Fu et al, 2022 [ 31 ] Hcy GWAS meta-analysis 44,147 European FA BMD GEFOS Consortium 8,143 European 11 IVW - 0.545 No (Not assessed) WM - 0.59 MR-Egger - 0.403 FN BMD GEFOS Consortium 32,735 9 IVW - 0.163 WM - 0.621 MR-Egger - 0.382 LS BMD GEFOS Consortium 28,498 9 IVW - 0.297 WM - 0.209 MR-Egger - 0.391 Heel BMD UK Biobank 142,487 11 IVW -
9.59E-04
WM -
0.013
MR-Egger - 0.268 Total body BMD GEFOS Consortium 66,628 11 IVW - 0.211 WM - 0.22 MR-Egger - 0.137 Total body BMD of age 0–15 GEFOS Consortium 11,807 11 IVW - 0.779 WM - 0.418 MR-Egger - 0.142 Total body BMD of age 15–30 GEFOS Consortium 4,180 11 IVW - 0.741 WM - 0.905 MR-Egger - 0.99 Total body BMD of age 30–45 GEFOS Consortium 10,062 11 IVW - 0.707 WM - 0.535 MR-Egger - 0.108 Total body BMD of age 45–60 GEFOS Consortium 18,805 11 IVW - 0.472 WM - 0.526 MR-Egger - 0.512 Total body BMD of age over 60 GEFOS Consortium 22,504 11 IVW - 0.342 WM - 0.276 MR-Egger - 0.383 Ma et al, 2022 [ 32 ] Hcy GWAS meta-analysis 44,147 European IA Published GWAS 7,495 cases; 71,934 controls European 9 IVW 1.124 (0.923, 1.368) 0.246 No (Not assessed) WM 1.204 (0.932, 1.555) 0.155 MR-Egger 1.236 (0.818, 1.869) 0.348 SAH 2,070 cases; 71,934 controls 9 IVW 1.104 (0.878, 1.387) 0.398 WM 1.239 (0.927, 1.657) 0.148 MR-Egger 1.291 (0.799, 2.085) 0.332 UIA 5,140 cases; 71,934 controls 7 IVW 1.126 (0.682, 1.858) 0.644 WM 1.091 (0.604, 1.969) 0.774 MR-Egger 1.103 (0.311, 3.913) 0.885 Xiong et al, 2022 [ 33 ] tHcy GWAS meta-analysis 44,147 European CKD CKDGen consortium and PAGE CKDGen consortium (41,395 cases; 439,303 controls)and PAGE (49,839) European 14 IVW 1.24 (1.07, 1.44)
< 0.05
No (Not assessed) eGFR IVW -
< 0.01
WM -
< 0.001
MR-Egger -
0.049
eGFR (Excluding diabetes patients) IVW -
0.008
WM -
0.002
MR-Egger - 0.076 Yu et al, 2022 [ 34 ] Hcy increase GWAS meta-analysis 44,147 European Grip strength (right) UK Biobank 461,089 European 7 IVW -
5.53×10
− 4
No (Not assessed) WM -
6.02E–03
MR-Egger - 0.69 Grip strength (left) 461,026 7 IVW -
1.45×10
− 5
WM -
6.80E–04
MR-Egger - 0.579 Walking pace 335,349 7 IVW -
3.18×10
− 4
WM -
5.66E–03
MR-Egger - 0.0747 ALM 450,243 7 IVW -
1.03×10
− 5
WM -
1.01E–03
MR-Egger - 0.226 Hcy decrease GWAS meta-analysis 44,147 European Grip strength (right) UK Biobank 461,089 European 4 IVW - 0.82 WM - 0.42 MR-Egger - 0.93 Grip strength (left) 461,026 3 IVW - 0.64 WM - 0.81 MR-Egger - 0.43 Walking pace 335,349 5 IVW - 0.61 WM - 0.39 MR-Egger - 0.67 ALM 450,243 4 IVW - 0.06 WM - 0.14 MR-Egger - 0.99 Yu et al, 2022 [ 35 ] Hcy GWAS meta-analysis 44,147 European SCZ GWAS meta-analysis 67,390 cases; 94,015 controls European 10 IVW 1.110 (1.028, 1.198)
2.74× 10
− 3
No (Not assessed) GSMR 1.115(1.041, 1.194)
1.73E-03
MDD Published GWAS 16,823 cases; 25,632 controls 13 IVW 0.948 (0.890, 1.009) 0.115 GSMR 0.951 (0.890, 1.017) 0.139 BD GWAS meta-analysis 41,917 cases; 371,549 controls 11 IVW 1.081 (0.998, 1.171) 0.054 GSMR 1.088 (1.006, 1.177)
0.037
BD-I GWAS meta-analysis 25,060 cases; 449,978 controls 13 IVW 1.133 (1.031, 1.245)
9.44×10
− 3
GSMR 1.144 (1.041, 1.257)
5.23E-03
BD-II GWAS meta-analysis 6,781 cases; 364,075 controls 13 IVW 0.977 (0.832, 1.147) 0.773 GSMR 0.977 (0.832, 1.147) 0.783 Chen et al, 2023 [ 36 ] Hcy GWAS meta-analysis 44,147 European Psoriasis FinnGen consortium 9,267 cases; 364,071 controls European 11 IVW 0.995 (0.863, 1.146) 0.941 No (Not assessed) WM 0.985 (0.834, 1.164) 0.862 MR-Egger 0.959 (0.704, 1.305) 0.795 Fu et al, 2023 [ 37 ] Hcy GWAS meta-analysis 44,147 European Birth weight Published GWAS 133,903 European 9 IVW - 0.06 Yes (p = 0.666) Childhood BMl 39,620 - 0.627 Yes (p = 0.607) WC adjusted for BMl 231,353 - 0.349 Yes (p = 0.473) WHR adjusted for BMI 210,082 -
0.03
Yes (p = 0.542) BMI 454,884 - 0.368 Yes (p = 0.01) BFFM 454,850 - 0.105 Yes (p = 0.57) BFM 454,137 - 0.221 Yes (p = 0.659) BFP 454,633 - 0.095 Yes (p = 0.592) Fu et al, 2023 [ 38 ] Hcy GWAS meta-analysis 44,147 European NAFLD Two meta-analyses of GWAS 8,434 cases; 770,180 controls European 9 IVW 1.21 (1.01, 1.43)
0.041
Yes (p = 0.156) (Ghodsian et al GWAS) WM 1.20 (0.97, 1.43) 0.067 NAFLD 1,483 cases; 17,781 controls IVW 1.52 (1.01, 2.13)
0.048
(Anstee et al GWAS) WM 1.50 (0.66, 2.33) 0.189 ALP UK Biobank 344,292 IVW -
0.039
No (Not assessed) WM - 0.074 MR-PRESSO - 0.071 ALT 344,136 IVW -
0.007
WM -
0.002
MR-PRESSO -
0.031
AST 342,990 IVW -
0.018
WM -
0.026
MR-PRESSO - 0.064 Hong et al, 2023 [ 39 ] Hcy GWAS meta-analysis 44,147 European Overall OA Published GWAS 177,517 cases; 649,173 controls European and East Asian 11 IVW 1.098 (1.044, 1.155)
< 0.001
No (Not assessed) WM 1.074 (1.000, 1.154)
0.05
MR-Egger 1.120 (0.941, 1.333) 0.233 Knee OA NR NR IVW 1.080 (1.000, 1.167)
0.05
WM 1.088 (0.979, 1.208) 0.118 MR-Egger 1.191 (0.917, 1.546) 0.223 Hip OA IVW 1.171 (1.057, 1.297)
0.002
WM 1.155 (1.001, 1.334)
0.049
MR-Egger 1.395 (0.952, 2.044) 0.126 Spine OA IVW 1.112 (0.995, 1.243) 0.062 WM 1.071 (0.921, 1.244) 0.374 MR-Egger 1.210 (0.868, 1.686) 0.289 Hand OA IVW 1.040 (0.907, 1.193) 0.574 WM 1.071 (0.884, 1.299) 0.483 MR-Egger 0.856 (0.506, 1.450) 0.578 Thumb OA IVW 1.057 (0.874, 1.278) 0.571 WM 1.083 (0.840, 1.395) 0.54 MR-Egger 0.836 (0.456, 1.532) 0.576 Hu et al, 2023 [ 40 ] Hcy GWAS meta-analysis 44,147 European COPD hospital admissions IEU Open GWAS 6,500 cases; 212,292 controls European 14 IVW 1.06 (0.91, 1.24) 0.42 No (Not assessed) WM 1.08 (0.88–1.33) 0.44 MR-Egger 1.10 (0.79–1.53) 0.57 Asthma/COPD 21,444 cases; 186,723 controls IVW 0.97 (089, 1.06) 0.55 WM 1.01 (0.89–1.15) 0.84 MR-Egger 1.09 (0.90–1.33) 0.4 COPD-related chronic (opportunistic) infections 234 cases; 186,723 controls IVW 1.50 (0.57, 3.99) 0.42 WM 2.32 (0.57–9.48) 0.24 MR-Egger 0.09 (0.05–1.54) 0.12 COPD/asthma/ILD-related pneumonia or pneumonia-derived septicemia 27,715 cases; 159,867 controls IVW 0.93 (0.86, 1.02) 0.13 WM 1.02 (0.91–1.14) 0.71 MR-Egger 1.07 (0.89–1.28) 0.47 COPD-related respiratory insufficiency 1,031 cases; 186,723 controls IVW 1.00 (0.70, 1.44) 0.99 WM 1.01 (0.62–1.67) 0.96 MR-Egger 1.28 (0.59–2.81) 0.54 Wang et al, 2023 [ 41 ] Hcy GWAS meta-analysis 44,147 European FA BMD GEFOS UK Biobank 8,143 European 8 IVW 0.957 (0.771, 1.188) 0.69 No (Not assessed) WM 0.942 (0.779, 1.139) 0.537 MR-Egger 1.084 (0.680, 1.729) 0.746 Lumbar BMD 28,498 7 IVW 0.856 (0.720, 1.016) 0.077 WM 0.844 (0.711, 1.001) 0.051 MR-Egger 0.635 (0.317, 1.274) 0.256 Heel BMD 142,487 8 IVW 0.960 (0.927, 0.990)
0.011
WM 0.967 (0.929, 1.005) 0.084 MR-Egger 0.981 (0.918, 1.049) 0.607 Wang et al, 2023 [ 42 ] Hcy GWAS meta-analysis 44,147 European Congestive heart failure Published GWAS 897 cases; 455,451 controls European 3 IVW 1.753 (0.674, 4.562) 0.25 No (Not assessed) WM 1.849 (1.014, 3.372)
0.045
MR-Egger 5.472(1.797, 16.665) 0.205 Cardiomyopathy FinnGen study 3100 cases; 156,711 controls 12 IVW 0.805 (0.583, 1.112) 0.189 WM 0.829(0.596, 1.154) 0.267 MR-Egger 1.126(0.576, 2.199) 0.736 Non-ischemic cardiomyopathy FinnGen study 11,400 cases; 1.751.752 controls 12 IVW 1.064 (0.927, 1.222) 0.379 WM 1.004 (0.845, 1.194) 0.961 MR-Egger 1.006(0.744, 1.361) 0.97 Gao et al, 2024 [ 43 ] Hcy GWAS meta-analysis 44,147 European GMV UK Biobank imaging database 7,916 European and White British 9 IVW 0.976 (0.871, 1.094) 0.068 No (Not assessed) WM 1.068 (0.938, 1.214) 0.324 MR-Egger 1.103 (0.895, 1.360) 0.388 8 IVW 0.858 (0.738, 0.999)
0.048
WM 0.836 (0.684, 1.021) 0.076 MR-Egger 0.725 (0.446, 1.178) 0.242 BV 9 IVW 0.958 (0.808, 1.135) 0.621 WM 1.078 (0.928, 1.252) 0.323 MR-Egger 1.113 (0.805, 1.540) 0.537 8 IVW 0.808 (0.652, 1.000)
0.049
WM 0.845 (0.651, 1.096) 0.202 MR-Egger 0.607 (0.301, 1.222) 0.211 Jin et al, 2024 [ 44 ] Hcy GWAS meta-analysis 44,147 European ASD iPSYCH-PGC 18,382 cases; 27,969 controls European 13 IVW 1.03 (0.92, 1.15) 0.63 No (Not assessed) WM 1.02 (0.88, 1.18) 0.84 MR-Egger 1.04 (0.82, 1.33) 0.74 Lin et al, 2024 [ 45 ] Hcy GWAS meta-analysis 44,147 European PCOS FinnGen GWAS 994; 165,817 controls European 14 IVW 1.163 (0.705, 1.919) 0.556 No (Not assessed) Tyrmi et al GWAS 3,609; 229,788 controls 0.988 (0.814, 1.200) 0.906 Day et al 4,138; 20,129 controls 1.903 (0.817, 1.464) 0.548 Abbreviations : OR, odds ratio; CI, confidential interval; NR, not reported; IVW, inverse variance weighted; WM, weighted median; wGRS, weighted genetic risk score; GSMR, Generalized Summary-data based Mendelian Randomization; Hcy, homocysteine; CAD, coronary artery disease; MI, myocardial infarction; AD, Alzheimer’s disease; IGAP, International Genomics of Alzheimer’s Project; tHcy, total homocysteine; SVS, small vessel stroke; LAS, large artery atherosclerosis stroke; CES, cardioembolism stroke; SAS, small artery occlusion stroke; AIS, all ischemic stroke; PHL, plasma homocysteine level; AF, atrial fibrillation; BRCA, breast cancer; PrCa, prostate cancer; RCC, renal cell carcinoma; MetS, metabolic syndrome; IS, ischemic stroke; IH, Intracerebral hemorrhage; SH, Subarachnoid hemorrhage; AA, Aortic aneurysm; AVS, Aortic valve stenosis; TIA, transient ischemic attack; VT, Venous thromboembolism; PVD, Peripheral vessel disease; ISGC, International Stroke Genetic Consortium; MS, multiple sclerosis; PD, Parkinson’s disease; ALS, amyotrophic lateral sclerosis; FTD, frontotemporal dementia; IMSGC, International Multiple Sclerosis Genetics Consortium; IPDGC, International Parkinson’s Disease Genomics Consortium; IALSGC, International Amyotrophic Lateral Sclerosis Genomics Consortium; IFLDC, International Frontotemporal Lobar Degeneration Collaboration; CHD, coronary heart disease; AMI, acute myocardial infarction; CARDIoGRAM, Coronary ARtery DIsease Genome wide Replication and Meta-analysis; C4D, Coronary Artery Disease; BMD, bone mineral density; FA: forearm; FN, femoral neck; LS, lumbar spine; eBMD, estimated heel BMD; GEFO, Genetic Factors for Osteoporosis Consortium; CAD, coronary artery disease; IA, intracranial aneurysm; SAH, subarachnoid hemorrhage; UIA, unruptured intracranial aneurysm; eGFR, estimated glomerular filtration rate; PAGE, Population Architecture using Genomics and Epidemiology; CKD, chronic kidney disease; ALM, appendicular lean mass; SCZ, schizophrenia; BD, bipolar disorder; MDD, major depressive disorder; NAFLD, nonalcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; T2DM, type 2 diabetes mellitus; BMI, body mass index; WHR, waist-to-hip ratio; WC, waist circumference; BFFM, body fat-free mass; BFP, body fat percentage; BFM, body fat mass; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; OA, osteoarthritis; COPD, chronic obstructive pulmonary disease; ILD, interstitial lung disease; OP, osteoporosis; BV, brain volume; GMV, gray matter volume; ASD, autism spectrum disorder; UKB, UK biobank; PCOS, Polycystic ovary syndrome

Summary of all published Mendelian randomization (MR) estimates for the association between homocysteine (Hcy) and multiple diseases

Abbreviations : OR, odds ratio; CI, confidential interval; NR, not reported; IVW, inverse variance weighted; WM, weighted median; wGRS, weighted genetic risk score; GSMR, Generalized Summary-data based Mendelian Randomization; Hcy, homocysteine; CAD, coronary artery disease; MI, myocardial infarction; AD, Alzheimer’s disease; IGAP, International Genomics of Alzheimer’s Project; tHcy, total homocysteine; SVS, small vessel stroke; LAS, large artery atherosclerosis stroke; CES, cardioembolism stroke; SAS, small artery occlusion stroke; AIS, all ischemic stroke; PHL, plasma homocysteine level; AF, atrial fibrillation; BRCA, breast cancer; PrCa, prostate cancer; RCC, renal cell carcinoma; MetS, metabolic syndrome; IS, ischemic stroke; IH, Intracerebral hemorrhage; SH, Subarachnoid hemorrhage; AA, Aortic aneurysm; AVS, Aortic valve stenosis; TIA, transient ischemic attack; VT, Venous thromboembolism; PVD, Peripheral vessel disease; ISGC, International Stroke Genetic Consortium; MS, multiple sclerosis; PD, Parkinson’s disease; ALS, amyotrophic lateral sclerosis; FTD, frontotemporal dementia; IMSGC, International Multiple Sclerosis Genetics Consortium; IPDGC, International Parkinson’s Disease Genomics Consortium; IALSGC, International Amyotrophic Lateral Sclerosis Genomics Consortium; IFLDC, International Frontotemporal Lobar Degeneration Collaboration; CHD, coronary heart disease; AMI, acute myocardial infarction; CARDIoGRAM, Coronary ARtery DIsease Genome wide Replication and Meta-analysis; C4D, Coronary Artery Disease; BMD, bone mineral density; FA: forearm; FN, femoral neck; LS, lumbar spine; eBMD, estimated heel BMD; GEFO, Genetic Factors for Osteoporosis Consortium; CAD, coronary artery disease; IA, intracranial aneurysm; SAH, subarachnoid hemorrhage; UIA, unruptured intracranial aneurysm; eGFR, estimated glomerular filtration rate; PAGE, Population Architecture using Genomics and Epidemiology; CKD, chronic kidney disease; ALM, appendicular lean mass; SCZ, schizophrenia; BD, bipolar disorder; MDD, major depressive disorder; NAFLD, nonalcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; T2DM, type 2 diabetes mellitus; BMI, body mass index; WHR, waist-to-hip ratio; WC, waist circumference; BFFM, body fat-free mass; BFP, body fat percentage; BFM, body fat mass; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; OA, osteoarthritis; COPD, chronic obstructive pulmonary disease; ILD, interstitial lung disease; OP, osteoporosis; BV, brain volume; GMV, gray matter volume; ASD, autism spectrum disorder; UKB, UK biobank; PCOS, Polycystic ovary syndrome

Fig. 2 Associations with genetically predicted higher levels of homocysteine (using the inverse-variance weighted method) in the systematic review of Mendelian randomization studies. CI, confidence interval; OR, odds ratio; SNPs, single nucleotide polymorphisms

Associations with genetically predicted higher levels of homocysteine (using the inverse-variance weighted method) in the systematic review of Mendelian randomization studies. CI, confidence interval; OR, odds ratio; SNPs, single nucleotide polymorphisms

Figure 2 . Associations with genetically predicted higher levels of homocysteine (using the inverse-variance weighted method) in the systematic review of Mendelian randomization studies. CI, confidence interval; OR, odds ratio; SNPs, single nucleotide polymorphisms.

Nervous system diseases

Genetically predicted total homocysteine (tHcy) levels demonstrated an inverse association with multiple sclerosis (MS) (OR = 0.780, 95% CI = 0.640–0.940) (Table  1 ; Fig.  2 ). One study found no causal relationship between plasma Hcy levels and brain atrophy, despite the use of nine genetic variants associated with Hcy levels. However, after excluding one SNP (rs1801133), the remaining eight SNPs suggested a potential causal relationship between plasma Hcy levels and both gray matter volume (GMV) and brain volume (BV) [ 43 ]. No heterogeneity was detected among the studies, and no significant associations were identified between genetically predicted Hcy levels and other neurological disorders.

Cardiovascular diseases

Elevated genetically predicted circulating tHcy levels were associated with an increased risk of several cardiovascular diseases, including: Small vessel stroke (SVS) (OR = 1.340, 95% CI = 1.130–1.580). Small artery occlusion stroke (SAS) (OR = 1.329, 95% CI = 1.047–1.612). Stroke (OR = 1.110, 95% CI = 1.030–1.200). Subarachnoid hemorrhage (SH) (OR = 1.260, 95% CI = 1.050–1.510). Ischemic stroke (IS) (OR = 1.110, 95% CI = 1.030–1.210) (Table  1 ; Fig.  2 ). Moderate heterogeneity was observed in analyses of stroke (I² > 50%) and ischemic stroke (IS) (I² > 50%), likely due to variations in data sources [ 26 ]. Specifically: The MEGASTROKE consortium includes multi-ethnic populations. The UK Biobank focuses on middle-aged and older individuals in the UK. The FinnGen study is derived from a genetically distinct Finnish population. These differences in ancestry, demographic characteristics, and methodological heterogeneity (e.g., phenotyping criteria, genotyping platforms) may collectively contribute to the observed inconsistencies between studies. Additionally, MR-Egger analysis for IS within the FinnGen dataset suggested potential pleiotropy [ 26 ]. No significant associations were detected between Hcy levels and 13 other cardiovascular conditions, including atrial fibrillation (AF).

Musculoskeletal system diseases

Individuals with genetically predicted higher Hcy levels showed an increased risk for all 13 musculoskeletal conditions and related markers examined (Table  1 ; Fig.  2 ). Positive associations were found between Hcy levels and osteoporosis with pathological fractures, forearm bone mineral density (FA BMD), body composition reflected by the waist-to-hip ratio (WHR) adjusted for BMI, soft tissue disorders, and knee osteoarthritis (OA). Conversely, Hcy levels were negatively correlated with heel BMD, grip strength in both dominant and non-dominant hands, and walking pace (Table  1 ; Fig.  2 ). There was slight heterogeneity in IVs related to grip strength (right) (Q_pval = 0.05) and walking pace (Q_pval = 0.02). Additionally, BMI appeared to significantly influence Hcy levels ( p  = 0.01), whereas Hcy had no significant effect on BMI (Table  1 ).

Urogenital diseases

Elevated Hcy levels were associated with a reduction in the estimated glomerular filtration rate (eGFR), contributing to the progression of chronic kidney disease (CKD) and subsequent renal function deterioration (Table  1 ; Fig.  2 ). Evidence testing revealed heterogeneity in CKD for the data from the CKDGen study (Q_pval < 0.05) [ 33 ]. However, the current findings do not support a causal relationship between Hcy levels and the risk of: Breast cancer (BRCA), Prostate cancer (PrCa), Renal cell carcinoma (RCC), and Polycystic ovary syndrome (PCOS). (Table  1 ).

Digestive system diseases

High plasma homocysteine level (PHL) may play a causal role in the etiology of gastric cancer (OR = 1.090, 95% CI = 1.010–1.180) (Table  1 ; Fig.  2 ). Furthermore, increased Hcy concentrations may increase the levels of relevant liver enzymes and may contribute to the risk of nonalcoholic fatty liver disease (NAFLD) (Table  1 ; Fig.  2 ). No heterogeneity was observed in any of the aforementioned studies.

Mental disorders

Elevated plasma Hcy levels were associated with a higher risk of: Schizophrenia (SCZ) (OR = 1.110, 95% CI = 1.028–1.198). Bipolar disorder-I (BD-I) (OR = 1.133, 95% CI = 1.031–1.245). However, no significant association was identified between Hcy levels and the risk of: Major depressive disorder (MDD), Bipolar disorder (BD), Bipolar disorder-II (BD-II), Autism spectrum disorder (ASD). (Table  1 ; Fig.  2 ).

Metabolic diseases

A significant correlation was observed between Hcy levels and an increased risk of developing metabolic syndrome (MetS) (OR = 2.054, 95% CI = 1.649–2.560), while no such association was found in the context of type 2 diabetes mellitus (T2DM) (Table  1 ; Fig.  2 ). Low heterogeneity was observed among studies investigating MetS [ 18 ].

Respiratory and dermal system diseases

No causal relationship was detected between genetically determined circulating Hcy levels and the risk of Psoriasis, Chronic obstructive pulmonary disease (COPD) (Table  1 ).

Discussion

This study examined the association between Hcy levels and 31 different outcome variables in MR studies, providing evidence for potential causality. Elevated Hcy levels were associated with an increased risk of several neurological, cardiovascular, musculoskeletal, urogenital, and digestive disorders, including SVS, SAS, stroke, SH, soft tissue disorders, OA, osteoporosis with pathological fractures, gastric cancer, CKD, SCZ, BD-I, and MetS. Conversely, higher Hcy levels were associated with a reduced risk of MS.

Hyperhomocysteinemia may elevate the risk of IS through multiple mechanisms. Excess Hcy can induce neuronal damage and blood-brain barrier dysfunction by triggering oxidative stress, protein homocysteinylation, and calcium dysregulation [ 48 ]. Additionally, Hcy-induced DNA hypomethylation can exacerbate apoptosis, neuronal cell death, and vascular dysfunction, increasing susceptibility to IS. Three studies [ 14 , 26 , 49 ] support the causal role of hereditary elevated Hcy levels in IS, and another study [ 50 ] suggests that hyperhomocysteinemia increases the risk of stroke recurrence in affected patients.

2 studies [ 30 , 39 ] consistently indicated that genetically elevated Hcy levels increase the risk of knee OA, despite discrepancies in statistical significance, likely due to sample size variations and population heterogeneity. Observational studies in Chinese populations [ 51 ] further corroborate this finding, demonstrating that patients with severe OA exhibit significantly higher serum Hcy levels than those with mild OA. Mechanistically, Hcy suppresses the SIRT1/AMPK/PGC-1α signaling pathway in chondrocytes, leading to mitochondrial dysfunction, oxidative stress, and apoptosis. Further mechanistic studies indicate that Hcy-mediated inhibition of the SIRT1/AMPK/PGC-1α/PPAR-γ axis upregulates NF-κB, COX-2, IL-8, and MMP-13, contributing to chondrocyte homeostasis disruption [ 52 ]. Similarly, studies by Fu [ 31 ] and Wang [ 41 ] suggest that Hcy may be a significant risk factor for heel fractures, potentially impairing bone quality by disrupting collagen cross-linking and destabilizing the collagen network [ 53 , 54 ]. However, further research is needed to confirm Hcy’s role in knee OA, heel bone mineral density (BMD), and heel fractures.

Although some studies report that Hcy negatively affects hip OA [ 39 ], another study found no significant evidence of this relationship [ 30 ]. Hcy-induced chondrocyte dysfunction, oxidative stress, and inflammation are hypothesized to contribute to hip OA progression [ 52 ]. However, ancestral differences in genetic studies—where Published GWAS included both European and East Asian populations, while UK Biobank included only European individuals—may explain inconsistencies. Additionally, differences in selected genetic variants (SNPs) as instrumental variables may also influence study outcomes. Further research is required to determine whether Hcy is a significant risk factor for hip OA, particularly in East Asian populations.

1 study [ 24 ] found that genetically reduced plasma Hcy levels correlated with higher FA-BMD, while increased Hcy levels were not significantly associated with FA-BMD. However, limitations such as a small number of instrumental variables and insufficient statistical power may have affected these results. Additionally, standardization of effect alleles prior to MR analysis is necessary to ensure accurate causal inferences.

This review identified divergent findings regarding the association between Hcy levels and NAFLD. Chen’ s study [ 28 ] found insufficient evidence to establish a causal link, whereas Fu’ s study [ 38 ] reported a positive genetic correlation between Hcy levels, NAFLD, and elevated liver enzymes. Discrepancies may stem from differences in genetic databases, which may reflect variations in genetic background, lifestyle, and dietary habits. Despite these inconsistencies, current evidence suggests a significant correlation between elevated Hcy levels and the incidence of NAFLD. This association may be explained by Hcy-induced oxidative stress, which may trigger iNOS activation and suppress eNOS expression in microvascular endothelial cells (MVECs) [ 55 ], leading to mitochondrial dysfunction, lipid peroxidation, hepatic inflammation, and fibrosis [ 56 , 57 ]. Future research should account for population differences to better elucidate Hcy’s role in NAFLD development.

Study limitations

This study has several limitations: Quality Variability: Among the included MR studies, 23 had a low risk of bias, 9 had a moderate risk, and 1 had a high risk, potentially affecting result reliability. Reverse Causality: Only two studies performed bidirectional MR analysis, limiting our ability to rule out reverse causation. Study Selection Bias: The search strategy may have excluded studies that employed MR as a secondary analysis, potentially overlooking relevant findings. Publication Bias: Restricting analysis to full-text, peer-reviewed publications may introduce bias by excluding conference papers, abstracts, and grey literature. Language Restriction: Only English-language studies were included, potentially limiting geographical representation. Predominance of Western Populations: Most studies focused on Western cohorts, limiting generalizability to other populations. Differences in environment, lifestyle, and healthcare systems may influence the applicability of findings to non-Western populations.

Conclusion

In summary, this study provides genetic evidence indicating that elevated homocysteine (Hcy) levels increase the risk of multiple conditions, including multiple sclerosis (MS), small artery occlusion stroke (SAS), subarachnoid hemorrhage (SH), hospital-diagnosed osteoarthritis (OA), soft tissue disorders, osteoporosis with pathological fractures, and gastric cancer. These findings offer substantial support for the role of Hcy in disease causation, with potential implications for the development of preventive measures and therapeutic strategies.

However, heterogeneity in genetic instruments, methodological quality variations, and conflicting results between studies create uncertainty regarding the causal relationship between Hcy levels and stroke, small vessel stroke (SVS), ischemic stroke (IS), chronic kidney disease (CKD), OA (overall, knee, and hip), nonalcoholic fatty liver disease (NAFLD), schizophrenia (SCZ), and bipolar disorder-I (BD-I). To confirm these findings, well-designed, long-term, large-scale randomized controlled trials (RCTs) are needed, particularly in non-European populations, to ensure the generalizability of results across diverse ethnic and demographic backgrounds.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 1

Supplementary Material 2

Supplementary Material 2