Physiogenomic comparison of human fat loss in response to diets restrictive of carbohydrate or fat

Does a Ketogenic Diet Have a Place Within Diabetes Clinical Practice? Review of Current Evidence and Controversies

Carbohydrate restriction has gained increasing popularity as an adjunctive nutritional therapy for diabetes management. However, controversy remains regarding the long-term suitability, safety, efficacy and potential superiority of a very low carbohydrate, ketogenic diet compared to current recommended nutritional approaches for diabetes management. Recommendations with respect to a ketogenic diet in clinical practice are often hindered by the lack of established definition, which prevents its capacity to be most appropriately prescribed as a therapeutic option for diabetes. Furthermore, with conflicted evidence, this has led to uncertainty amongst clinicians on how best to support and advise their patients. This review will explore whether a ketogenic diet has a place within clinical practice by reviewing current evidence and controversies.

Metabolic Syndrome: An Overview on Its Genetic Associations and Gene-Diet Interactions

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene-diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook.

The Personalized Nutrition Study (POINTS): evaluation of a genetically informed weight loss approach, a Randomized Clinical Trial

Weight loss (WL) differences between isocaloric high-carbohydrate and high-fat diets are generally small; however, individual WL varies within diet groups. Genotype patterns may modify diet effects, with carbohydrate-responsive genotypes losing more weight on high-carbohydrate diets (and vice versa for fat-responsive genotypes). We investigated whether 12-week WL (kg, primary outcome) differs between genotype-concordant and genotype-discordant diets. In this 12-week single-center WL trial, 145 participants with overweight/obesity were identified a priori as fat-responders or carbohydrate-responders based on their combined genotypes at ten genetic variants and randomized to a high-fat (n = 73) or high-carbohydrate diet (n = 72), yielding 4 groups: (1) fat-responders receiving high-fat diet, (2) fat-responders receiving high-carbohydrate diet, (3) carbohydrate-responders receiving high-fat diet, (4) carbohydrate-responders receiving high-carbohydrate diet. Dietitians delivered the WL intervention via 12 weekly diet-specific small group sessions. Outcome assessors were blind to diet assignment and genotype patterns. We included 122 participants (54.4 [SD:13.2] years, BMI 34.9 [SD:5.1] kg/m2, 84% women) in the analyses. Twelve-week WL did not differ between the genotype-concordant (-5.3 kg [SD:1.0]) and genotype-discordant diets (-4.8 kg [SD:1.1]; adjusted difference: -0.6 kg [95% CI: -2.1,0.9], p = 0.50). With the current ability to genotype participants as fat- or carbohydrate-responders, evidence does not support greater WL on genotype-concordant diets. ClinicalTrials identifier: NCT04145466.

In the context of the triple burden of malnutrition: A systematic review of gene-diet interactions and nutritional status

Genetic background interacts with dietary components to modulate nutritional health status. This study aimed to review the evidence for gene-diet interactions in all forms of malnutrition. A comprehensive systematic literature search was conducted through April 2021 to identify observational and intervention studies reporting the effects of gene-diet interactions in over-nutrition, under-nutrition and micronutrient status. Risk of publication bias was assessed using the Quality Criteria Checklist and a tool specifically designed for gene-diet interaction research. 167 studies from 27 populations were included. The majority of studies investigated single nucleotide polymorphisms (SNPs) in overnutrition (n = 158). Diets rich in whole grains, vegetables, fruits and low in total and saturated fats, such as Mediterranean and DASH diets, showed promising effects for reducing obesity risk among individuals who had higher genetic risk scores for obesity, particularly the risk alleles carriers of FTO rs9939609, rs1121980 and rs1421085. Other SNPs in MC4R, PPARG and APOA5 genes were also commonly studied for interaction with diet on overnutrition though findings were inconclusive. Only limited data were found related to undernutrition (n = 1) and micronutrient status (n = 9). The findings on gene-diet interactions in this review highlight the importance of personalized nutrition, and more research on undernutrition and micronutrient status is warranted.

Genetic variants for personalised management of very low carbohydrate ketogenic diets

The ketogenic diet (KD) is a low-carbohydrate, high-fat, adequate-protein diet proven to be effective for the reversal of obesity, metabolic syndrome and type 2 diabetes, and holding therapeutic potential for the prevention and treatment of other chronic diseases. Genetic and dynamic markers of KD response may help to identify individuals most likely to benefit from KD and point to individuals at higher risk for adverse health outcomes. Here, we provide a clinician-friendly review of state-of-the-art research on biomarkers of KD response for a variety of outcomes including weight loss, body composition and cognitive performance drawing data from both intervention trials and case reports of rare inborn errors of metabolism. We also present a selection of the most promising candidate genes to evaluate in future studies and discuss key aspects of study design and variant interpretation that may help accelerate the implementation of these biomarkers in clinical practice.

Genomic Influence in the Prevention of Cardiovascular Diseases with a Sterol-Based Treatment

Raised serum cholesterol concentration is a well-established risk factor in cardiovascular disease. In addition, genetic load may have an indirect influence on cardiovascular risk. Plant-based sterol-supplemented foods are recommended to help reduce the serum low-density lipoprotein cholesterol level. The objective was to analyse the influence of different polymorphisms in hypercholesterolemia patients following a dietary treatment with plant sterols. A randomised double-blind cross-over controlled clinical trial was carried out in 45 people (25 women). Commercial milk, containing 2.24 g of sterols, was ingested daily during a 3-week period, and then the same amount of skim milk, without sterols, was consumed daily during the 3-week placebo phase. Both phases were separated by a washout period of 2 weeks. At the beginning and end of each phase, blood draws were performed. Genes LIPC C-514T and APOA5 C56G are Ser19Trp carriers and greatly benefit from sterol intake in the diet. LIPC C-514T TT homozygous carriers had lower low-density lipoprotein cholesterol (LDL-c) levels than CC homozygote and CT heterozygote carriers after the ingestion of plant sterols (p = 0.001). These two genes also showed statistically significant changes in total cholesterol levels (p = 0.025; p = 0.005), and no significant changes in high-density lipoprotein (HDL) cholesterol levels (p = 0.032; p = 0.003), respectively. No statistically significant differences were observed for other genes. Further studies are needed to establish which genotype combinations would be the most protective against hypercholesterolemia.

Comparative physiogenomic analyses of weight loss in response to 2 modes of bariatric surgery: demonstration with candidate neuropsychiatric and cardiometabolic genes

BACKGROUND

Surgical weight loss response is variable, with suboptimal outcomes in some patients. We hypothesized that genetic biomarkers may be related to weight change.

METHODS

We tested 330 single nucleotide polymorphisms (SNPs) in genes relevant to metabolic regulation in 161 patients whose decrease in body mass index (BMI), 1 year after laparoscopic adjustable gastric banding (LAGB) or Roux-en-Y gastric bypass (RYGB), was small (lowest quartile response) or large (highest quartile response). LAGB patients whose BMI decreased≤4.7 or≥10.2 units comprised groups I (n = 43) and II (n = 40), respectively. RYGB patients whose BMI decreased≤13.6 or≥19.8 units comprised groups III (n = 39) and IV (n = 39), respectively. Within each surgery, SNPs with large differences in reference allele frequency (z score>2, corresponding to values displaced 2 standard deviations [SD] from the mean for all SNPs) in low versus high quartiles, were identified. We compared reference allele frequencies, within surgical procedure, using the χ(2) test (using Bonferroni correction for multiple testing).

RESULTS

The mean percent excess weight losses (±SD) corresponding to groups I, II, III, and IV were: 16 (±12), 64 (±30), 55 (±16), and 75 (±17), respectively. SNPs with z score>2 were identified in genes involved in LAGB response, lipid metabolic regulation (APOE, rs439401; APOC4, rs2288911), neural processes (DRD3, rs167771; HTR3 B, rs3758987), and xeno- or endobiotic metabolism (CYP3 A4, rs12333983); and for RYGB response, in lipid transport (SCARB1, rs10846744), folate metabolism (MTHFR, rs2066470), regulation of glycolysis in immune cells (HIF1 A, rs1951795), vitamin K cycling (VKORC1, rs2359612), and xeno- or endobiotic metabolism (CYP3 A4, rs2242480). For LAGB response, APOE SNP frequencies were significantly different.

CONCLUSIONS

With further validation, information derived from patient DNA may be useful to predict surgical weight loss outcomes and guide selection of surgical approach.

Genetic Association Study of Angiotensin II Receptor Types 1 (A168G) and 2 (T1247G and A5235G) Polymorphisms in Breast Carcinoma among Brazilian Women

BACKGROUND

Many types of cancer are associated with polymorphisms of the renin-angiotensin system. Our aim was to assess possible association between single-nucleotide polymorphisms (SNPs) of the angiotensin II receptor types 1 (A168G), and 2 (T1247G and A5235G) with breast cancer.

PATIENTS AND METHODS

242 participating subjects were genotyped and allocated to case or control groups.

RESULTS

Genotype distribution (in %) was: for AGTR1 (A168G): AA, AG, GG = 61, 30, 09 for cases, and 69, 25, 06 for controls (p = 0.55); for AGTR2 (T1247G): TT, TG, GG = 84, 12, 04 for cases, and 81, 17, 02 for controls (p = 0.45); for AGTR2 (A5235G): AA, AG, GG = 32, 67, 01 for cases, and 53, 28, 19 for controls (p < 0.0001). Women carrying genotypes AA/AG in the intronic region of angiotensin II type 2 receptor had an 11-fold higher risk of breast cancer than GG carriers.

CONCLUSIONS

Many types of cancer have been associated with polymorphisms of the renin-angiotensin system. For SNP A5235G, the GG genotype seems to be protective against breast cancer. The other 2 SNPs showed no association. However, SNPs T1247G and A5235G were associated with at least 1 clinical variable, with G being a predictor of better outcome. The use of SNPs A5235G and T1247G (the latter to a lesser degree) as genetic markers should be considered.

AGTR2 gene polymorphism is associated with muscle fibre composition, athletic status and aerobic performance

Muscle fibre type is a heritable trait and can partly predict athletic success. It has been proposed that polymorphisms of genes involved in the regulation of muscle fibre characteristics may predispose the muscle precursor cells of a given individual to be predominantly fast or slow. In the present study, we examined the association between 15 candidate gene polymorphisms and muscle fibre type composition of the vastus lateralis muscle in 55 physically active, healthy men. We found that rs11091046 C allele carriers of the angiotensin II type 2 receptor gene (AGTR2; involved in skeletal muscle development, metabolism and circulatory homeostasis) had a significantly higher percentage of slow-twitch fibres than A allele carriers [54.2 (11.1) versus 45.2 (10.2)%; P = 0.003]. These data indicate that 15.2% of the variation in muscle fibre composition of the vastus lateralis muscle can be explained by the AGTR2 genotype. Next, we investigated the frequencies of the AGTR2 alleles in 2178 Caucasian athletes and 1220 control subjects. The frequency of the AGTR2 C allele was significantly higher in male and female endurance athletes compared with power athletes (males, 62.7 versus 51.7%, P = 0.0038; females, 56.6 versus 48.1%, P = 0.0169) and control subjects (males, 62.7 versus 51.0%, P = 0.0006; elite female athletes, 65.1 versus 55.2%, P = 0.0488). Furthermore, the frequency of the AGTR2 A allele was significantly over-represented in female power athletes (51.9%) in comparison to control subjects (44.8%, P = 0.0069). We also found that relative maximal oxygen consumption was significantly greater in male endurance athletes with the AGTR2 C allele compared with AGTR2 A allele carriers [n = 28; 62.3 (4.4) versus 57.4 (6.0) ml min(-1) kg(-1); P = 0.0197]. Taken together, these results demonstrate that the AGTR2 gene C allele is associated with an increased proportion of slow-twitch muscle fibres, endurance athlete status and aerobic performance, while the A allele is associated with a higher percentage of fast-twitch fibres and power-oriented disciplines.

Physiogenomic analysis of CYP450 drug metabolism correlates dyslipidemia with pharmacogenetic functional status in psychiatric patients

AIMS

To investigate associations between novel human cytochrome P450 (CYP450) combinatory (multigene) and substrate-specific drug metabolism indices, and elements of metabolic syndrome, such as low density lipoprotein cholesterol (LDLc), high density lipoprotein cholesterol (HDLc), triglycerides and BMI, using physiogenomic analysis.

METHODS

CYP2C9, CYP2C19 and CYP2D6 genotypes and clinical data were obtained for 150 consecutive, consenting hospital admissions with a diagnosis of major depressive disorder and who were treated with psychotropic medications. Data analysis compared clinical measures of LDLc, HDLc, triglyceride and BMI with novel combinatory and substrate-specific CYP450 drug metabolism indices.

RESULTS

We found that a greater metabolic reserve index score is related to lower LDLc and higher HDLc, and that a greater metabolic alteration index score corresponds with higher LDLc and lower HLDc values. We also discovered that the sertraline drug-specific indices correlated with cholesterol and triglyceride values.

CONCLUSIONS

Overall, we demonstrated how a multigene approach to CYP450 genotype analysis yields more accurate and significant results than single-gene analyses. Ranking the individual with respect to the population represents a potential tool for assessing risk of dyslipidemia in major depressive disorder patients who are being treated with psychotropics. In addition, the drug-specific indices appear useful for modeling a variable of potential relevance to an individual's risk of drug-related dyslipidemia.

Physiogenomic analysis of statin-treated patients: domain-specific counter effects within the ACACB gene on low-density lipoprotein cholesterol?

AIM

Administered at maximal dosages, the most common statins--atorvastatin, simvastatin and rosuvastatin--lower low-density lipoprotein cholesterol (LDLC) by an average of 37-57% in patients with primary hypercholesterolemia. We hypothesized novel genetic underpinnings for variation in LDLC levels in the context of statin therapy.

MATERIALS & METHODS

Genotyping of 384 SNPs in 202 volunteers from a lipid outpatient clinic was accomplished and LDLC levels obtained from chart records. The SNPs were distributed across 222 genes representing physiological pathways such as general metabolism, cholesterol biochemistry, cardiovascular function, inflammation, neurobiology and cell proliferation. We discovered significant associations with LDLC levels for the rs34274 SNP (p < 0.0002) and for rs2241220 (p < 0.008) in the acetyl-coenzyme A carboxylase beta (ACACB) gene. When corrected for multiple testing, the false-discovery rate associated with rs34274 was 0.076 (significance threshold: 0.10) and for rs2241220 the false-discovery rate was 0.93 (not significant). The acetyl coenzyme A carboxylase beta enzyme synthesizes malonyl coenzyme A, an essential substrate for hepatic fatty acid synthesis and an inhibitor of fatty acid oxidation.

RESULTS

The SNPs were in weak linkage disequilibrium (D = 0.302). Minor alleles at these sites demonstrate opposing influences on LDLC; the C>T substitution at rs34724 is a risk marker and the C>T substitution at rs2241220 a protective marker for LDLC levels. These SNPs hypothetically influence enzymatic activity through different mechanisms, rs34274 through the PII promoter and rs2241220 via alteration of the protein's responsiveness to allosteric influence.

CONCLUSION

Physiogenomic evidence suggests a novel link between LDLC levels and the regulation of fatty acid metabolism. The findings complement previously discovered novel SNP relationships to myalgia (pain) and myositis (serum creatine kinase activity). By genotyping for myositis, myalgia and LDLC levels, a physiogenomic model may be developed to help clinicians maximize effectiveness and minimize side effects in prescribing statins.

Physiogenomic analysis of the Puerto Rican population

AIMS

Admixture in the population of the island of Puerto Rico is of general interest with regards to pharmacogenetics to develop comprehensive strategies for personalized healthcare in Latin Americans. This research was aimed at determining the frequencies of SNPs in key physiological, pharmacological and biochemical genes to infer population structure and ancestry in the Puerto Rican population.

MATERIALS & METHODS

A noninterventional, cross-sectional, retrospective study design was implemented following a controlled, stratified-by-region, random sampling protocol. The sample was based on birthrates in each region of the island of Puerto Rico, according to the 2004 National Birth Registry. Genomic DNA samples from 100 newborns were obtained from the Puerto Rico Newborn Screening Program in dried-blood spot cards. Genotyping using a physiogenomic array was performed for 332 SNPs from 196 cardiometabolic and neuroendocrine genes. Population structure was examined using a Bayesian clustering approach as well as by allelic dissimilarity as a measure of allele sharing.

RESULTS

The Puerto Rican sample was found to be broadly heterogeneous. We observed three main clusters in the population, which we hypothesize to reflect the historical admixture in the Puerto Rican population from Amerindian, African and European ancestors. We present evidence for this interpretation by comparing allele frequencies for the three clusters with those for the same SNPs available from the International HapMap project for Asian, African and European populations.

CONCLUSION

Our results demonstrate that population analysis can be performed with a physiogenomic array of cardiometabolic and neuroendocrine genes to facilitate the translation of genome diversity into personalized medicine.