# Common Genetic Variations Involved in the Inter-Individual Variability of Circulating Cholesterol Concentrations in Response to Diets: A Narrative Review of Recent Evidence

Mohammad M H Abdullah, Itzel Vazquez-Vidal, David J Baer, James D House, Peter J H Jones, Charles Desmarchelier

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Mohammad M H Abdullah, Itzel Vazquez-Vidal, David J Baer, James D House, Peter J H Jones, et al. Common Genetic Variations Involved in the Inter-Individual Variability of Circulating Cholesterol Concentrations in Response to Diets: A Narrative Review of Recent Evidence. Nutrients, 2021, 13 (2), pp.695. 10.3390/nu13020695. [hal-03224469](https://hal-03224469)

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Review

# Common Genetic Variations Involved in the Inter-Individual Variability of Circulating Cholesterol Concentrations in Response to Diets: A Narrative Review of Recent Evidence

Mohammad M. H. Abdullah<sup>1 ID</sup>, Itzel Vazquez-Vidal<sup>2</sup>, David J. Baer<sup>3</sup>, James D. House<sup>4 ID</sup>, Peter J. H. Jones<sup>5</sup>
and Charles Desmarchelier<sup>6,* ID</sup>

1 Department of Food Science and Nutrition, Kuwait University, Kuwait City 10002, Kuwait; mohamad.abdullah@ku.edu.kw

2 Richardson Centre for Functional Foods & Nutraceuticals, University of Manitoba, Winnipeg, MB R3T 6C5, Canada; itzel_vazquez25@yahoo.com

3 United States Department of Agriculture, Agricultural Research Service, Beltsville, MD 20705, USA; david.baer@usda.gov

4 Department of Food and Human Nutritional Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada; j_house@umanitoba.ca

5 Nutritional Fundamentals for Health, Vaudreuil-Dorion, QC J7V 5V5, Canada; peterjones@nfh.ca

6 Aix Marseille University, INRAE, INSERM, C2VN, 13005 Marseille, France

* Correspondence: charles.desmarchelier@univ-amu.fr

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**Citation:** Abdullah, M.M.H.; Vazquez-Vidal, I.; Baer, D.J.; House, J.D.; Jones, P.J.H.; Desmarchelier, C. *Common Genetic Variations Involved in the Inter-Individual Variability of Circulating Cholesterol*

*Concentrations in Response to Diets: A Narrative Review of Recent Evidence.* *Nutrients* **2021**, *13*, 695. https://doi.org/10.3390/nu13020695

Academic Editor:
David Cameron-Smith

Received: 31 December 2020

Accepted: 12 February 2021

Published: 22 February 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

**Abstract:** The number of nutrigenetic studies dedicated to the identification of single nucleotide polymorphisms (SNPs) modulating blood lipid profiles in response to dietary interventions has increased considerably over the last decade. However, the robustness of the evidence-based science supporting the area remains to be evaluated. The objective of this review was to present recent findings concerning the effects of interactions between SNPs in genes involved in cholesterol metabolism and transport, and dietary intakes or interventions on circulating cholesterol concentrations, which are causally involved in cardiovascular diseases and established biomarkers of cardiovascular health. We identified recent studies (2014–2020) that reported significant SNP–diet interactions in 14 cholesterol-related genes (*NPC1L1*, *ABCA1*, *ABCG5*, *ABCG8*, *APOA1*, *APOA2*, *APOA5*, *APOB*, *APOE*, *CETP*, *CYP7A1*, *DHCR7*, *LPL*, and *LIPC*), and which replicated associations observed in previous studies. Some studies have also shown that combinations of SNPs could explain a higher proportion of variability in response to dietary interventions. Although some findings still need replication, including in larger and more diverse study populations, there is good evidence that some SNPs are consistently associated with differing circulating cholesterol concentrations in response to dietary interventions. These results could help clinicians provide patients with more personalized dietary recommendations, in order to lower their risk for cardiovascular disease.

**Keywords:** lipids; gene-diet interaction; personalized nutrition; single nucleotide polymorphism; genetic variant; cardiovascular diseases; nutrigenetics

## 1. Introduction

Personalized nutrition is the next frontier for the food and health industries. Presently, consumers report high expectations for the role proper genetic information could play in their dietary choices for the prevention and treatment of chronic diseases [1,2]. Cardiovascular disease (CVD) is still the leading cause of death globally, and it is estimated that 90% of cases are preventable, with healthy diet considered as the first line of intervention [3,4]. Lowering of blood lipid concentrations is a major target in both the primary and secondary prevention of CVD, but high interindividual variability exists in response to any given dietary intervention [5].
Genome-wide association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with the variability of fasting blood cholesterol concentrations. These genetic variations have been estimated to explain about 30% of total variance [6,7]. Yet, the application of the results to personalized dietary recommendations is not straightforward because these studies usually do not consider the effect of diet. Several clinical trials have investigated the relationship between dietary interventions and blood lipid concentrations, considering the genetic characteristics of the participants. However, by design, they usually only focus on individual SNPs, resulting in a relatively low explained genetic variance [8,9]. A greater part of the variability in blood lipid concentrations could be explained by the additive effects of several SNPs, which, taken individually, may only have small, and barely significant, effects [10,11]. While numerous studies have reported SNPs that are significantly associated with blood cholesterol concentrations in response to various diets [8], there is a need to review additional data generated in this field.

The objective of this narrative review is, thus, to summarize recent findings of inter-
actions between individual SNPs in major cholesterol-related genes and dietary intakes,
relative to shaping circulating cholesterol concentrations. The review also highlights stud-
ies that used combinations of SNPs to increase the explained variability in cholesterol
concentrations following dietary interventions. Looking at the sum of evidence accumu-
lated in the field enables discussion of what is still missing in order to put this knowledge
into practice.

## 2. Search Process and Criteria

For the purpose of this review, we considered only genes that are explicitly involved
in cholesterol absorption, metabolism, and transport pathways (Figure 1). A systematic
search was utilized, and gene-diet interaction studies relative to the genes of interest
were retrieved, with no restriction on study design, dietary protocol, population, or qual-
ity throughout the preliminary search. Searches were performed on articles published
between 1 January 2014 (as a follow-up to our previous review on the topic [8]) and
30 September 2020 using the MEDLINE (PubMed) database, and searching string varia-
tions of the following keywords: (diet OR gene-diet OR dietary) AND (cholesterol) AND
(SNP OR polymorphism OR genetic variant). A total of 291 articles were identified and
examined individually to exclude research articles that did not report statistically signif-
icant cholesterol responses to gene-diet interactions, did not present clear associations,
or did not provide data details. With the exclusion of all review articles, animal studies,
and articles in languages other than English, as well as those considering factors other than
diet, such as physical activity, alcohol intake, smoking, and others, a total of 21 distinct
research articles were eligible for inclusion in the individual SNP-diet interaction analysis
(Section 3), and four articles were eligible for the combinatory patterns of SNPs analysis
(Section 4) below.

The following sections present statistically significant findings regarding the effects
of interactions between SNPs (taken individually or in combinatory patterns) and dietary
intakes on circulating cholesterol concentrations in observational studies and dietary
interventions. Nomenclature for all genes in this work is reported according to international
standards of the Human Genome Organization (HUGO) [12], with description of variants
at the DNA level and reference to SNPs as rs#-xx homozygotes or rs#-x alleles, even when
authors of some of the reviewed articles reported variants as defined by their encoding
amino acid changes, using the 3-letter code or the 1-letter code, with no mention of the rs#
for their SNPs. Where applicable in the sections below, the meanings of such amino acid
codes are addressed.
<figure><img src="image_5.png" /><figcaption>**Figure 1.** Summary of genes of lipid metabolism and transport pathways involved in the variability of circulating cholesterol concentrations in response to diets. Genes displayed are those for which significant SNP-diet interactions have been reported recently (2014–2020). ABCA1, ATP binding cassette subfamily A member 1; ABCG5/8, ATP binding cassette subfamily G member 5/8; APOA1, apolipoprotein A1; APOA2, apolipoprotein A2; APOA5, apolipoprotein A5; APOB, apolipoprotein B; APOE, apolipoprotein E; CE, cholesteryl esters; CETP, cholesteryl ester transfer protein; CYP7A1, cholesterol 7-alpha-hydroxylase; DHCR7, 7-dehydrocholesterol reductase; HDL, high-density lipoprotein; IDL, intermediate-density lipoprotein; LDL, low-density lipoprotein; LPL, lipoprotein lipase; LIPC, hepatic lipase; NPC1L1, NPC1 like intracellular cholesterol transporter 1; TG, triglycerides; VLDL, very-low-density lipoprotein</figcaption></figure>

**3. Studies Investigating the Effect of SNPs Taken Individually**

In this section, a summary of the recent evidence on statistically significant gene-
diet interactions is presented considering individual SNP data (Table 1). This approach
has been the most widely utilized in research and reported in the literature due to both
technical and statistical reasons. For instance, sequencing and genotyping techniques,
such as commercially available SNP assays and PCR methods, are presently low-cost
and easy-to-implement. Moreover, dietary interventions are typically expensive to carry
out, and usually have relatively low sample sizes, resulting in limited statistical power.
Nonetheless, they allow for identification of new genetic associations based on known
or predicted SNP functions. Importantly, the SNP-diet interactions identified in clinical
settings also constitute good candidates for building genetic risk scores (GRS) of cumula-
tive SNPs, aiming at predicting practical changes in biomarkers of health in response to
dietary intakes.
<table><caption>**Table 1.** Summary of epidemiological and dietary intervention studies reporting significant effects of individual SNP-diet interactions on circulating cholesterol concentrations.</caption><thead><tr><td>Author</td><td>Gene</td><td>SNP</td><td>Study Design</td><td>Diet</td><td>Population and Ethnicity</td><td>Major Cholesterol Outcomes</td></tr></thead><tbody><tr><td>Jacobo-Albavera et al. (2015) [13]</td><td>ABCA1</td><td>rs9282541</td><td>Cross-sectional</td><td>Dietary CHO and fat intakes</td><td>1598 premenopausal females, Mexicans</td><td>HDL-C concentrations negatively correlated with CHO intake and positively correlated with fat intake in T allele carriers but not CC homozygotes</td></tr><tr><td>Liu et al. (2014) [14]</td><td>ABCA1</td><td>rs2230806</td><td>Dietary intervention</td><td>7-d of washout diet followed by 6-d of high-CHO/low-fat diet</td><td>56 healthy adults, Chinese</td><td>Lower LDL-C/HDL-C concentration ratios in A allele male carriers and GG female homozygotes after vs. before high-CHO/low-fat diet</td></tr><tr><td>Abdullah et al. (2016) [15]</td><td>ABCG5</td><td>rs6720173</td><td>Crossover</td><td>Dairy vs. dairy-free diets</td><td>101 healthy adults, Canadians</td><td>Higher TC and LDL-C concentrations in GG homozygotes vs. C allele carriers after 3 servings/d of dairy vs. dairy-free diets</td></tr><tr><td>Granado-Lorencio et al. (2014) [16]</td><td>ABCG8</td><td>rs6544718</td><td>Crossover</td><td>750 µg β-cryptoxanthin and 1.5 g/d PS, single and combined</td><td>19 postmenopausal females, Spanish</td><td>Lower TC concentrations in CC homozygotes vs. T allele carriers after β-cryptoxanthin + PS combined intake</td></tr><tr><td>de Luis et al. (2018) [17]</td><td>APOA1</td><td>rs670</td><td>Dietary intervention</td><td>Hypocaloric diet of one arm</td><td>82 obese adults, Spanish</td><td>Lower HDL-C concentrations in GG homozygotes vs. A allele carriers at baseline and after hypocaloric diet</td></tr><tr><td>de Luis et al. (2019) [18]</td><td>APOA1</td><td>rs670</td><td>Dietary intervention</td><td>Hypocaloric high-fat vs. low-fat diets</td><td>282 obese adults, Spanish</td><td>Higher HDL-C concentrations in A allele carriers vs. GG homozygotes at baseline and after both high-fat and low-fat diets</td></tr><tr><td>Noorshahi et al. (2016) [19]</td><td>APOA2</td><td>rs5082</td><td>Cross-sectional</td><td>Dietary SFA intake (>28.5 g/d), assessed by FFQ</td><td>697 type 2 diabetic adults, Iranians</td><td>Higher LDL-C/HDL-C concentration ratio in CC homozygotes vs. T allele carriers with higher SFA intake</td></tr><tr><td>Dominguez-Reyes et al. (2015) [20]</td><td>APOA5</td><td>rs662799</td><td>Cross-sectional</td><td>Dietary fat intake, assessed by FFQ</td><td>200 young normal-weight and obese adults, Mexicans</td><td>Lower HDL-C concentrations and higher PUFA intake in C allele carriers vs. TT homozygotes</td></tr><tr><td>Lim et al. (2014) [21]</td><td>APOA5</td><td>rs662799</td><td>Cross-sectional</td><td>Dietary intake, assessed by 24-h recall and FFQ</td><td>1128 premenopausal females, Koreans</td><td>Lower HDL-C concentrations in CC homozygotes with higher total energy intake (≥2001 kcal/d)</td></tr><tr><td>Doo et al. (2015) [22]</td><td>APOB</td><td>rs1469513</td><td>Cross-sectional ('KoGES' Study)</td><td>Total energy and macronutrient intake, assessed by FFQ</td><td>6470 adults, Koreans</td><td>Higher TC and LDL-C concentrations in G allele carriers with higher energy or fat intake, and in AA homozygotes with higher CHO intake</td></tr></tbody></table>
<table><caption>Table 1. *Cont.*</caption><thead><tr><td>Author</td><td>Gene</td><td>SNP</td><td>Study Design</td><td>Diet</td><td>Population and Ethnicity</td><td>Major Cholesterol Outcomes</td></tr></thead><tbody><tr><td>Shatwan et al. (2017) [23]</td><td>APOE</td><td>rs1064725</td><td>16-wk parallel dietary intervention ('DIVAS' Study)</td><td>Isoenergetic diets rich in SFA, MUFA, or n-6 PUFA</td><td>120 adults with moderate cardiovascular risk, Caucasians</td><td>Lower TC concentrations only in TT homozygotes after MUFA-rich diet vs. SFA-rich or n-6 PUFA-rich diets</td></tr><tr><td>Weber et al. (2016) [24]</td><td>APOE</td><td>rs429258 rs7412</td><td>Cross-sectional (German Diabetes Study)</td><td>Dietary fat intake, assessed by FFQ</td><td>348 diabetics, Germans</td><td>Lower LDL-C concentrations in APOE ε2 carriers with lower vs. higher intake frequencies of butter, cream cake, French fries, or alcoholic beverages</td></tr><tr><td>Mackay et al. (2015) [25]</td><td>APOE</td><td>rs429258 rs7412</td><td>Crossover</td><td>2 g/d of PS</td><td>63 mildly hypercholesterolemic adults, Canadians</td><td>Greater reduction in LDL-C concentrations after PS intake in APOE ε4 vs. APOE ε3 carriers</td></tr><tr><td>Griffin et al. (2018) [26]</td><td>APOE</td><td>rs429258 rs7412</td><td>24-wk five-arm parallel dietary intervention ('RISCK' Study)</td><td>Replacing SFA with either MUFA or carbohydrate of high or low GI</td><td>389 adults at increased risk of developing MetS, white Caucasians</td><td>Greater decreases in TC concentrations in carriers of E4 vs. E3/E3 when SFA was replaced with low GI carbohydrate on a lower fat diet, and an increase in TC concentrations when SFA was replaced with MUFA and high GI carbohydrates</td></tr><tr><td>Garcia-Rios et al. (2016) [27]</td><td>CETP</td><td>rs3764261</td><td>1-y dietary intervention ('CORDIOPREV' Study)</td><td>Mediterranean diet (35% fat, 22% MUFA) vs. low-fat diet (28% fat, 12% MUFA)</td><td>424 MetS subjects, Spanish</td><td>Higher HDL-C concentrations after Mediterranean diet in T allele carriers vs. GG homozygotes</td></tr><tr><td>Hosseini-Esfahani et al (2019) [28]</td><td>CETP</td><td>rs3764261</td><td>Population-based prospective design (Tehran Lipid and Glucose Study)</td><td>Usual dietary intake, assessed by FFQ</td><td>4700 adults, Iranians</td><td>Lower TC concentrations and higher fish intakes in T allele carriers vs. GG homozygotes after 3.6 years of follow-up</td></tr><tr><td>Abdullah et al. (2016) [15]</td><td>CYP7A1</td><td>rs3808607</td><td>Crossover</td><td>Dairy vs. dairy-free diets</td><td>101 healthy adults, Canadians</td><td>Higher TC concentrations in G allele carriers vs. TT homozygotes after 3 servings/d of dairy vs. dairy-free diets</td></tr><tr><td>Mackay et al. (2015) [25]</td><td>CYP7A1</td><td>rs3808607</td><td>Crossover</td><td>2 g/d of PS</td><td>63 mildly hypercholesterolemic adults, Canadians</td><td>Greater reduction in LDL-C concentrations after PS intake in GG vs. TT homozygotes</td></tr><tr><td>Wang et al. (2016) [29]</td><td>CYP7A1</td><td>rs3808607</td><td>Crossover</td><td>Barley β-glucan vs. control diet</td><td>30 mildly hypercholesterolemic adults, Canadians</td><td>Lower TC concentrations after 3 g/d of high molecular weight barley β-glucan in G allele carriers vs. TT homozygotes</td></tr></tbody></table>
<table><caption>**Table 1. Cont.**</caption><thead><tr><th>Author</th><th>Gene</th><th>SNP</th><th>Study Design</th><th>Diet</th><th>Population and Ethnicity</th><th>Major Cholesterol Outcomes</th></tr></thead><tbody><tr><td>Abdullah et al. (2016) [15]</td><td>DHCR7</td><td>rs760241</td><td>Crossover</td><td>Dairy vs. dairy-free diets</td><td>101 healthy adults, Canadians</td><td>Higher LDL-C concentrations in A allele carriers vs. GG homozygotes after 3 servings/d of dairy vs. dairy-free diets</td></tr><tr><td>Zhu et al. (2014) [30]</td><td>LPL</td><td>rs326</td><td>Dietary intervention</td><td>7-d of washout diet followed by 6-d of high-CHO (70% energy)/low-fat (~14% energy) diet</td><td>56 healthy Chinese Han youth</td><td>Higher HDL-C concentrations in G allele male carriers after vs. before high-CHO/low-fat diet</td></tr><tr><td>Ayyappa et al. (2017) [31]</td><td>LPL</td><td>rs1121923</td><td>Cross-sectional (Chennai Urban Rural Epidemiological Study)</td><td>Dietary intakes, assessed by FFQ</td><td>788 type 2 diabetes cases and 1057 controls, Asian Indians</td><td>Higher HDL-C concentrations in T allele carriers with high fat diet vs. CC homozygotes</td></tr><tr><td>Smith et al. (2017) [32]</td><td>LIPC</td><td>rs1800588</td><td>Crossover</td><td>Comparing a high-fat Western diet and a low-fat traditional Hispanic diet</td><td>42 adults, Caribbean Hispanic descent</td><td>Higher HDL-C concentrations in CC homozygotes after high-fat Western diet (39% energy) vs. low-fat traditional Hispanic diet (20% energy)</td></tr><tr><td>Xu et al. (2015) [33]</td><td>LIPC</td><td>rs2070895</td><td>2-y randomized weight-loss dietary intervention ('POUNDS LOST' Study)</td><td>Dietary intakes</td><td>743 overweight or obese adults, multiethnic groups</td><td>Higher TC concentrations after high fat intake, and higher HDL-C concentrations after low fat intake, in A allele carriers vs. GG homozygotes</td></tr><tr><td>Granado-Lorencio et al. (2014) [16]</td><td>NPC1L1</td><td>rs2072183</td><td>Crossover</td><td>750 µg β-cryptoxanthin and 1.5 g/d PS, single and combined</td><td>19 postmenopausal females, Spanish</td><td>Higher TC concentrations in CC homozygotes vs. G allele carriers after PS intake only</td></tr></tbody></table>

**Abbreviations:** ABC, ATP-binding cassette subfamily; APO, apolipoproteins; CETP, cholesteryl ester transfer protein; CHO, carbohydrate; DHCR7, 7-dehydrocholesterol reductase; CYP7A1, cholesterol 7-alpha-hydroxylase; FFQ, food frequency questionnaire; GI, glycemic index; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; LPL, lipoprotein lipase; LIPC, hepatic lipase; MetS, metabolic syndrome; MUFA, monounsaturated fatty acids; SFA, saturated fatty acids; SNP, single nucleotide polymorphism; PUFA, polyunsaturated fatty acids; NPC1L1, NPC1 like intracellular cholesterol transporter 1; PS, plant sterols; TC, total cholesterol.
### 3.1. SNPs in Genes Encoding Transporters Involved in Cholesterol Absorption

NPC1 like intracellular cholesterol transporter 1 (NPC1L1) is an apical multi-pass membrane protein that mediates the transport of sterols into enterocytes and hepatocytes through clathrin-mediated endocytosis, and is essential for cholesterol trafficking [34–36]. It is now well-established that dietary plant sterols (PS) can inhibit intestinal cholesterol absorption through several mechanisms, such as competition for incorporation into mixed micelles, hydrolysis of esters by digestive enzymes, enterocyte uptake by NPC1L1, and incorporation into chylomicrons [34,37]. In a randomized crossover supplementation study involving 19 post-menopausal females, participants carrying the CC genotype at rs2072183 (a synonymous variant with leucine at 272, published as L272L) in NPC1L1 showed significantly different changes in serum TC and LDL-C concentrations (0.38 ± 0.29 and 0.33 ± 0.29 mmol/L, respectively) compared to carriers of the G allele (−0.29 ± 0.10 and −0.18 ± 0.12 mmol/L, respectively) after consuming for four weeks a beverage providing 1.5 g PS/d [16]. Of note, these differences were no longer significant when an outlier in the participants homozygous for the minor allele was excluded from the statistical analysis.

ATP-binding cassette subfamily A1 (ABCA1) is a basolateral membrane protein that transports cholesterol and phospholipids out of enterocytes and hepatocytes, which are then collected by apolipoprotein A1 (encoded by APOA1) to form nascent HDL particles [38,39]. A 2015 cross-sectional study involving 1598 premenopausal Mexican females found that serum HDL-C concentrations were negatively correlated with carbohydrate intake (*r* = −0.362), and positively correlated with fat intake (*r* = 0.357), in carriers of the T allele at rs9282541 in ABCA1 (published as RC/CC in the R230C missense variant, as defined by the amino acid change) but not in those carrying the CC genotype (published as RR in R230C variant) [13]. This variant is restricted to the Americas, where its presence explains up to 4% of the variation in HDL-C concentrations [40]. In an intervention study, 56 healthy Chinese adults received a washout diet where carbohydrate contributed 54% of energy for 7 d, followed by a high-carbohydrate/low-fat diet where carbohydrate and fat contributed 70% and 14% of energy, respectively, for 6 d [14]. Males carrying the A (published as K) allele and females carrying the GG (published as RR) genotype at rs2230806 in ABCA1 (G1051A; published as R219K, a missense variant, as defined by the amino acid change) displayed lower LDL-C/HDL-C concentration ratios (1.08 ± 0.27 vs. 1.48 ± 0.64 in males, and 1.01 ± 0.18 vs. 1.37 ± 0.33 in females) after the high-carbohydrate/low-fat diet [14].

The ATP-binding cassette subfamily G member 5 and 8 (ABCG5/G8) genes encode two transporters (ABCG5 and ABCG8) that are responsible for the excretion of sterols by hepatocytes and enterocytes [41]. Rare and common genetic variations in ABCG5/G8 have been linked to increased intestinal absorption of cholesterol and PS [42–44]. In a 2016 randomized crossover study by our group, involving 101 normocholesterolemic adults, the ABCG5 rs6720173-GG homozygotes had higher serum TC (change: 0.18 ± 0.06 vs. −0.07 ± 0.07 mmol/L) and LDL-C (change: 0.17 ± 0.05 vs. −0.06 ± 0.07 mmol/L) concentrations relative to rs6720173-C allele carriers after three servings/d of dairy (low-fat milk, low-fat yogurt, and regular cheddar cheese) versus a dairy-free diets for 4 wk each [15]. These data replicate, to some extent, previous associations described among Spanish children [45], where male carriers of the ABCG5 rs6720173-G allele had higher plasma TC and LDL-C concentrations with a daily intake of 14.3–34.1 g saturated fatty acids (SFA) compared to CC homozygotes [45]. Another crossover multiple-dose supplementation study with beta-cryptoxanthin and PS in healthy postmenopausal females showed that carriers of the CC genotype of ABCG8 rs6544718 (published as A632V, a missense variant, as defined by the amino acid change) had lower serum TC concentrations (−0.34 ± 0.09 mmol/L) compared to carriers of the T allele (0.08 ± 0.20 mmol/L) after consuming a beverage providing 1.5 g/d of PS plus 750 µg beta-cryptoxanthin over 4 wk [16].

### 3.2. SNPs in Genes Encoding Apolipoproteins

Apolipoprotein A1 (APOA1) encodes a protein that drives maturation of HDL particles [46,47]. A weight loss intervention of one arm involving 82 obese patients showed that
carriers of the GG genotype at rs670 in *APOA1* had lower serum HDL-C concentrations compared to A allele carriers, both at baseline (1.43 ± 0.25 vs. 1.50 ± 0.24 mmol/L) and after 12 wk (1.37 ± 0.21 vs. 1.45 ± 0.23 mmol/L) on a hypocaloric diet (reduction of 500 kcal/d) [17]. A similar 12 wk hypocaloric intervention involving 282 obese participants, by the same group, reported improvements in HDL-C concentrations among the rs670-A allele carriers versus GG homozygotes at baseline, as well as after both high-fat (1.42 ± 0.23 vs. 1.27 ± 0.18 mmol/L) and low-fat (1.53 ± 0.21 vs. 1.40 ± 0.23 mmol/L) diets [18].

*Apolipoprotein A2 (APOA2)* encodes the second most common protein found in HDL particles [48]. A 2016 cross-sectional study involving 697 diabetic participants from Tehran, Iran, reported that carriers of the *APOA2* rs5082-CC genotype who, based on a semi-quantitative food frequency questionnaire (FFQ) analysis, had higher SFA intake (>28.5 g/d, considering mean SFA intake of the study population as cutoff point) and displayed a higher LDL-C/HDL-C concentration ratio (2.27 ± 0.72 vs. 2.04 ± 0.63) compared to carriers of the T allele [19].

*Apolipoprotein A5 (APOA5)* encodes an essential protein component of several lipoproteins such as VLDL, HDL, and chylomicrons [49]. A number of meta-analyses have demonstrated that SNPs in *APOA5* may be associated with increased risk for CVD, where, in particular, carriers of the *APOA5* rs662799-C allele exhibit higher concentrations of TC and TG, and lower concentrations of HDL-C compared to non-carriers [50,51]. In a cross-sectional study conducted among young Mexicans (18–25 y), participants carrying the rs662799-C allele and who traditionally consumed a diet higher in PUFAs, with median (percentile 25–75) of 10 (8–12) g/d vs. 8 (6–12) g/d also showed lower serum HDL-C concentrations compared to TT homozygotes (1.1 (0.9–1.2) mmol/L vs. 1.2 (1.0–1.4) mmol/L); although this was not reported by the authors as part of their gene–diet interaction data [20]. In another cross-sectional study involving 1128 premenopausal Korean females, among participants who had total energy intakes ≥2001 kcal/d, based on a 24-h recall method and a semi-quantitative FFQ data analysis, rs662799-CC homozygotes displayed lower serum HDL-C concentrations (~1.16 vs. 1.42 mmol/L) compared to T allele carriers [21].

*Apolipoprotein B (APOB)* encodes a protein that modulates the formation and blood clearance of LDL particles and triglyceride (TG)-rich lipoproteins. Circulating apoB-48 and apoB-100 concentrations are well-known biomarkers of cardiovascular health [52]. A cross-sectional study including 6470 Korean adults showed that among those who reported consuming higher levels of energy (≥1983.7 kcal/d), based on a semi-quantitative FFQ analysis, carriers of the minor allele (G) at rs1469513 in *APOB* had higher plasma TC (+2.42%) and LDL-C (+1.96%) concentrations compared to the AA homozygotes; similar TC response was seen with higher fat intake (≥19.9% energy), where the difference between G allele carriers and AA homozygotes was 2.04% [22]. In contrast, homozygotes for the A allele who consumed carbohydrates in excess of 64.9% of energy exhibited higher TC (+1.81%) and LDL-C (+2.80%) concentrations compared to G allele carriers [22].

*Apolipoprotein E* is one of the major proteins involved in the transport of cholesterol and TG within the circulation [53]. A 2017 retrospective analysis of 120 participants enrolled in the DIVAS study, a parallel design based on a food-exchange model of SFA, monounsaturated fatty acid (MUFA), and polyunsaturated fatty acid (PUFA) intakes in free-living individuals for 16 wk, reported that only *APOE* rs1064725-TT homozygotes, but not G allele carriers, showed a reduction in serum TC concentrations after the MUFA diet (−0.71 ± 1.88 mmol/L) compared to the SFA (0.34 ± 0.55 mmol/L) or n-6 PUFA diets (−0.08 ± 0.73 mmol/L) [23]. A German diabetes study evaluated the interaction between dietary patterns, using FFQ data, and *APOE* polymorphisms in 348 diabetic patients, where among carriers of the *APOE* ε2 isoform (E2/E2, E2/E3; rs429258: TT, rs7412: TT/CT), lower versus higher consumption frequencies of butter, cream cake, French fries, or alcoholic beverages were independently associated with a 40% reduction in serum LDL-C concentrations [24]. In a randomized crossover design involving 63 mildly hypercholesterolemic individuals who consumed 2 g/d of PS for 28 d, carriers of the *APOE* ε4 isoform had a greater reduction in serum LDL-C concentrations (−0.31 ± 0.07 mmol/L
vs. -0.13 ± 0.05 mmol/L) compared to carriers of the APOE ε3 isoform [25]. This study also reported an interaction between APOE and CYP7A1-rs3808607, where participants of all genosets, except for CYP7A1-rs3808607 T/T + APOE ε3, showed reductions in LDL-C concentrations in response to PS consumption [25]. Furthermore, in a secondary analysis of data from the RISCK study, a 24-wk five-arm parallel intervention involving 389 adults, carriers of E4 relative to E3/E3 showed greater decreases in plasma TC concentrations (-0.28 ± 0.13 mmol/L) when SFA was replaced with low glycemic index (GI) carbohydrate on a lower fat diet, and a relative increase in TC concentrations (0.30 ± 0.14 mmol/L) when SFA was replaced with MUFA and high GI carbohydrates [26].

### 3.3. Genes Encoding Additional Proteins Involved in the Cholesterol Metabolic Pathway

Cholesteryl ester transfer protein (CETP) exchanges TG from lipoproteins (VLDL or LDL) with cholesteryl esters from HDL particles [54]. In the CORDIOPREV clinical trial involving 424 Spanish participants with metabolic syndrome (MetS) who received a Mediterranean diet rich in fat from olive oil (35% fat, 22% MUFA) or a low-fat diet (28% fat, 12% MUFA), carriers of the minor allele (T) at rs3764261 in CETP showed higher plasma HDL-C concentrations (1.06 ± 0.03 vs. 0.98 ± 0.02 mmol/L) compared to GG homozygotes after 1 y on the Mediterranean diet, but not after the low-fat diet [27]. The CETP rs3764261-diet interaction was more recently investigated among 4700 adults from the Tehran Lipid and Glucose Study, a population-based prospective design, where among carriers of the T (published as A) allele, serum TC concentrations decreased from 8.02 to 5.58 mmol/L as fish intake increased from <3.6 g/d (quartile 1) through >14.9 g/d (quartile 4) compared to GG (published as CC) homozygotes, after 3.6 years of follow-up [28].

Cholesterol 7-alpha hydroxylase, encoded by *CYP7A1*, is a rate-limiting enzyme in the classic bile acid synthesis pathway in the liver. *CYP7A1* rs3808607 has been associated with inter-individual variability in circulating cholesterol concentrations in response to dietary intakes. For instance, after 4 wk on a crossover design with dairy versus dairy-free diets, we have previously shown that carriers of the rs3808607-G allele had higher serum TC concentrations (ranging between 0.20 ± 0.06 and 0.28 ± 0.12 mmol/L for GT and GG genotypes, respectively) compared to TT homozygotes (-0.11 ± 0.08 mmol/L) [15]. In response to PS intake, however, the rs3808607-GG homozygotes showed greater a reduction in serum LDL-C concentrations (-0.46 ± 0.12 vs. -0.05 ± 0.07 mmol/L) compared to the TT homozygotes [25]. In yet another crossover design involving 30 mildly hypercholesterolemic adults who received a breakfast that contained either 3 g of high molecular weight barley β-glucan or a control diet daily for 5 wk each, carriers of the rs3808607-G allele showed greater reduction in serum TC concentrations (-0.58 and -0.70 mmol/L for GT and GG genotypes, respectively) compared to TT homozygotes (-0.31 mmol/L) [29].

The 7-dehydrocholesterol reductase, encoded by *DHCR7*, is the enzyme that catalyzes the terminal reaction of cholesterol synthesis in the liver. In response to dairy intervention, carriers of the *DHCR7* rs760241 minor allele (A) showed higher serum LDL-C concentrations (0.26 ± 0.08 vs. 0.06 ± 0.05 mmol/L) relative to GG homozygotes [15]. To our knowledge, this study by members of our group was the first, and thus far only, evidence of such interaction between the *DHCR7* SNP rs760241 and dietary intake.

Lipoprotein lipase, encoded by *LPL*, is an enzyme catalyzing the hydrolysis of TG from apoB-containing lipoproteins. A 2014 dietary intervention involving 56 healthy young Chinese showed that only male carriers of the *LPL* rs326 minor allele (G) had an increase in plasma HDL-C concentrations (1.32 ± 0.27 vs. 1.21 ± 0.21 mmol/L) after versus before a 6-d diet of high-carbohydrate (70.1% energy)/low-fat (13.7% energy) [30]. In the cross-sectional Chennai Urban Rural Epidemiological Study, involving type 2 diabetes cases and controls from India, carriers of the *LPL* rs1121923 minor allele (T) exhibited higher serum HDL-C concentrations (1.2 vs. 1.1 mmol/L) compared to CC homozygotes after consumption of a higher fat diet (3rd tertile: 28.4 ± 2.5% energy), as assessed by a semi-quantitative FFQ [31]. No differences were observed among genotypic groups consuming a diet providing less than 23.5% of energy from fat.
Hepatic lipase, encoded by *LIPC*, is an enzyme involved in reverse cholesterol transport. In a 2017 crossover, randomized controlled trial involving 42 Caribbean Hispanics, carriers of the *LIPC* rs1800588 major allele (C) had higher plasma HDL-C concentrations (1.3 ± 0.03 vs. 1.1 ± 0.04 mmol/L during phase 1, and 1.4 ± 0.03 vs. 1.2 ± 0.03 mmol/L during phase 2 of the trial) after consuming a high-fat Western diet (39% energy) compared to a low-fat traditional Hispanic diet (20% energy) for 4 wk each, whereas no difference was observed between Western and Hispanic diets among TT homozygotes [32]. In the POUNDS LOST trial, a long-term weight-loss intervention with diets varying in macronutrient composition, overweight and obese carriers of the *LIPC* rs2070895 minor allele (A) showed an increase in serum TC concentrations (β ± SE: 0.19 ± 0.07 mmol/L) on a high-fat diet (40% energy) and a slight decrease in HDL-C concentrations (β ± SE: -0.04 ± 0.02 mmol/L) on a low-fat diet (20% energy) compared to rs2070895-GG homozygotes at 2 yr of the intervention [33].

**4. Combinatory Patterns of SNPs Influencing Changes in Blood Cholesterol Concentrations in Response to Dietary Interventions**

Recently, the availability of low-cost genetic testing kits and new bioinformatic tools has allowed significant progress in understanding the complex interplay between genetics and diet. Development of GRS, in which various SNPs information is aggregated, offers a valuable approach to explain a higher percentage of variability in blood cholesterol profiles compared to analyzing individual SNPs [10,11].

In a study published in 2015, Justesen et al. investigated the effect of the interaction between GRS and lifestyle factors, including diet, on fasting serum lipid concentrations in a population-based Danish cohort comprised of 5961 male and female participants (mean age = 46.1 y, mean BMI = 26.3 kg/m²) [55]. GRS of increased TC (74 loci), LDL-C (58 loci), or triglyceride (TG) (39 loci), and decreased HDL-C (71 loci) concentrations were built based on SNPs previously identified following GWAS of circulating fasting lipid concentrations. Dietary habits were estimated following dietary questionnaires and were classified as unhealthy, moderately healthy, and healthy. There was no significant effect of GRS and dietary habit interaction on baseline fasting serum cholesterol concentrations. The effect of specific components of the diet was not investigated.

In a secondary analysis of data from the Food4Me study, a multi-country European online randomized controlled intervention exploring the potential for personalized nutrition to enhance nutritional and health outcomes, the authors built a GRS based on 14 SNPs previously identified in GWAS of components of MetS and that showed a significant association with any component of MetS at baseline of the intervention [56]. Thus, most selected SNPs had no existing association with cholesterol metabolism and transport. They found that after 6 months of intervention, among the 1263 male and female participants (mean age = 40.8 y, mean BMI = 25.4 kg/m²), those with a low GRS exhibited a significantly higher decrease in TC concentrations, compared to those with a high GRS (approximately -0.1 mmol/L), independently of Mediterranean diet adherence level.

In a secondary analysis of data from a randomized crossover study [15], members of our group demonstrated a combinatory action of three SNPs in cholesterol-related genes, where among 101 normocholesterolemic participants (age = 18–69 y), carriers of the genotypic combination of ABCG5 rs6720173-C, CYP7A1 rs3808607-TT, and DHCR7 rs760241-GG exhibited a maximal reduction in serum LDL-C concentrations relative to a combination of rs6720173-GG, rs3808607-G, and rs760241-A genotypes (change: -0.37 ± 0.12 vs. 0.38 ± 0.14 mmol/L), following a blended dairy (3 servings/d for 4 wk) versus dairy-free intervention [57].

In a 2019 study, Guevara-Cruz et al. investigated the effect of the interaction between a GRS and a dietary intervention on serum HDL-C concentrations in 67 Mexican adults (20–60 y) with a BMI ≥ 25 kg/m² and who had at least three out of five positive criteria for MetS [58]. The dietary intervention consisted in the consumption for 2.5 months of a diet following the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) guidelines, i.e., low in saturated fats (<7% energy) and cholesterol
reported in this review, and those previously reported [8], are good starting candidates to build GRS aiming at predicting changes in blood cholesterol concentrations in response to dietary interventions. As an additional tool to advance the field, the availability of artificial intelligence and machine-learning approaches for identifying panels of SNPs, which in combination could better predict an individual's lipid response to dietary interventions, offer tremendous potential [61]. The latter methods may allow a more rapid advancement of the field of personalized nutrition.

**Author Contributions:** Conceptualization, M.M.H.A., I.V.-V., D.J.B., P.J.H.J. and C.D.; methodology and formal analysis, M.M.H.A., I.V.-V., D.J.B., P.J.H.J. and C.D.; writing—original draft preparation, I.V.-V., M.M.H.A., and C.D.; writing—review and editing, M.M.H.A., I.V.-V., D.J.B., J.D.H., P.J.H.J. and C.D.; Project administration and funding acquisition, P.J.H.J. and J.D.H. All authors have read and agreed to the published version of the manuscript.

**Funding:** I.V.-V. received research funding from the International Life Sciences Institute North America (Grant 320188). Supported by the Dietary Lipids Committee, North American Branch of the International Life Sciences Institute (ILSI North America). ILSI North America is a public, nonprofit scientific foundation that provides a forum to advance understanding of scientific issues related to the nutritional quality and safety of the food supply by sponsoring research programs, educational seminars and workshops, and publications. ILSI North America receives support primarily from its industry membership. ILSI NA was not involved in the review process and provided no comments on the interpretation of the findings.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** Disclosure I.V.-V. received stipend support from the grant received from ILSI NA. No other conflicts of interest are declared. M.M.H.A. declares no conflict of interest. D.J.B. is the Government liaison to the International Life Sciences Institute, North America Committee on Dietary Lipids. He receives no compensation in that role. J.D.H. serves as Co-Chair of the Canadian Leadership Team for ILSI NA, and currently serves as administrative lead for the research grant received from ILSI NA in support of this review. P.J.H.J. has received research grants from Nutritional Fundamentals for Health Inc., Mitacs, and the International Life Science Institute. He also owns stock in Nutritional Fundamentals for Health Inc. C.D. declares no conflict of interest.

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