THOC5: a novel gene involved in HDL-cholesterol metabolism

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced high-density lipoprotein cholesterol, and impaired glucose tolerance. It poses a significant public health concern, as individuals with MetS are at an increased risk of developing cardiovascular diseases and type 2 diabetes. Early and accurate identification of individuals at risk for MetS is essential. Various machine learning approaches have been employed to predict MetS, such as logistic regression, support vector machines, and several boosting techniques. However, these methods use MetS as a binary status and do not consider that MetS comprises five components. Therefore, a method that focuses on these characteristics of MetS is needed. In this study, we propose a multi-task deep learning model designed to predict MetS and its five components simultaneously. The benefit of multi-task learning is that it can manage multiple tasks with a single model, and learning related tasks may enhance the model's predictive performance. To assess the efficacy of our proposed method, we compared its performance with that of several single-task approaches, including logistic regression, support vector machine, CatBoost, LightGBM, XGBoost and one-dimensional convolutional neural network. For the construction of our multi-task deep learning model, we utilized data from the Korean Association Resource (KARE) project, which includes 352,228 single nucleotide polymorphisms (SNPs) from 7729 individuals. We also considered lifestyle, dietary, and socio-economic factors that affect chronic diseases, in addition to genomic data. By evaluating metrics such as accuracy, precision, F1-score, and the area under the receiver operating characteristic curve, we demonstrate that our multi-task learning model surpasses traditional single-task machine learning models in predicting MetS.

Zinc Improves Semen Parameters in High-Fat Diet-Induced Male Rats by Regulating the Expression of LncRNA in Testis Tissue

This study aimed to identify differentially expressed LncRNAs in testis tissue of male rats induced by high-fat diet and their changes after zinc supplementation, by constructing a high-fat feeding rat model, and then supplemented with zinc, and observed the expression of LncRNA in three groups of normal, high-fat fed, and zinc-intervened rats. Experimental studies show that the semen parameters of male rats with high-fat diet were decreased but recovered after zinc supplementation, and the related LncRNA also changed. Zinc may improve the high-fat diet-induced reduction of semen parameters by changing the expression of related LncRNA.

A Nutrigenetic Update on CETP Gene–Diet Interactions on Lipid-Related Outcomes

Purpose of Review

An abnormal lipid profile is considered a main risk factor for cardiovascular diseases and evidence suggests that single nucleotide polymorphisms (SNPs) in the cholesteryl ester transfer protein (CETP) gene contribute to variations in lipid levels in response to dietary intake. The objective of this review was to identify and discuss nutrigenetic studies assessing the interactions between CETP SNPs and dietary factors on blood lipids.

Recent Findings

Relevant articles were obtained through a literature search of PubMed and Google Scholar through to July 2021. An article was included if it examined an interaction between CETP SNPs and dietary factors on blood lipids. From 49 eligible nutrigenetic studies, 27 studies reported significant interactions between 8 CETP SNPs and 17 dietary factors on blood lipids in 18 ethnicities. The discrepancies in the study findings could be attributed to genetic heterogeneity, and differences in sample size, study design, lifestyle and measurement of dietary intake. The most extensively studied ethnicities were those of Caucasian populations and majority of the studies reported an interaction with dietary fat intake. The rs708272 (TaqIB) was the most widely studied CETP SNP, where ‘B1’ allele was associated with higher CETP activity, resulting in lower high-density lipoprotein cholesterol and higher serum triglycerides under the influence of high dietary fat intake.

Summary

Overall, the findings suggest that CETP SNPs might alter blood lipid profiles by modifying responses to diet, but further large studies in multiple ethnic groups are warranted to identify individuals at risk of adverse lipid response to diet.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11883-022-00987-y.

Genome-Wide Identification of Rare and Common Variants Driving Triglyceride Levels in a Nevada Population

Clinical conditions correlated with elevated triglyceride levels are well-known: coronary heart disease, hypertension, and diabetes. Underlying genetic and phenotypic mechanisms are not fully understood, partially due to lack of coordinated genotypic-phenotypic data. Here we use a subset of the Healthy Nevada Project, a population of 9,183 sequenced participants with longitudinal electronic health records to examine consequences of altered triglyceride levels. Specifically, Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records to identify: (1) rare and common single-variant genome-wide associations; (2) gene-based associations using a Sequence Kernel Association Test; (3) phenome-wide associations with triglyceride levels; and (4) pleiotropic variants linked to triglyceride levels. The study identified 549 significant single-variant associations (p < 8.75 × 10-9), many in chromosome 11's triglyceride hotspot: ZPR1, BUD13, APOC3, APOA5. A well-known protective loss-of-function variant in APOC3 (R19X) was associated with a 51% decrease in triglyceride levels in the cohort. Sixteen gene-based triglyceride associations were identified; six of these genes surprisingly did not include a single variant with significant associations. Results at the variant and gene level were validated with the UK Biobank. The combination of a single-variant genome-wide association, a gene-based association method, and phenome wide-association studies identified rare and common variants, genes, and phenotypes associated with elevated triglyceride levels, some of which may have been overlooked with standard approaches.

Polymorphism of the THOC5 of the transcription/export multiprotein complex and its correlation with the lipid and metabolic profile in middle-aged women

The transcription/export complex (TREX) is formed by a core called THO. These are necessary for the transcription and packaging of messenger RNA and its subsequent nuclear exportation. Studies have correlated THO-specific polymorphisms with abnormalities of HDL-C metabolism. To correlate lipid and metabolic parameters with the genetic variants of the rs8135828 polymorphism of the THOC5 gene in middle-aged women. DNA was extracted from the whole blood of 183 women aged 40-65 and tested for the rs8135828 polymorphism of the THOC5 gene using real-time PCR. HDL-C, LDL-C, triglyceride, and total cholesterol levels, as well as other metabolic parameters, were correlated with the polymorphism genotypes: GG, AG, and AA. Mean age of women was 50.6 ± 6.3 years, 54.6% were postmenopausal and 16.4% had the metabolic syndrome. GG was the most frequently determined genotype (62.3%). There were no differences in lipid levels according to genotypes; although there was a trend for lower HDL-C levels for the AA and AG + AA genotypes. Those with the AG and AG + AA genotypes displayed significantly higher glucose levels (p = .02 and p = .002, respectively); with a trend toward a higher metabolic syndrome prevalence and increased abdominal perimeters in both variants (AG and AG + AA). The AG genotype was related to higher glucose levels but not with abnormal lipid parameters. There is a need for more research in this regard.

Lipid-related genetic polymorphisms significantly modulate the association between lipids and disability progression in multiple sclerosis

OBJECTIVE

To investigate whether lipid-related or body mass index (BMI)-related common genetic polymorphisms modulate the associations between serum lipid levels, BMI and disability progression in multiple sclerosis (MS).

METHODS

The association between disability progression (annualised Expanded Disability Status Scale (EDSS) change over 5 years, ΔEDSS) and lipid-related or BMI-related genetic polymorphisms was evaluated in a longitudinal cohort (n=184), diagnosed with MS. We constructed a cumulative genetic risk score (CGRS) of associated polymorphisms (p<0.05) and examined the interactions between the CGRS and lipid levels (measured at baseline) in predicting ΔEDSS. All analyses were conducted using linear regression.

RESULTS

Five lipid polymorphisms (rs2013208, rs9488822, rs17173637, rs10401969 and rs2277862) and one BMI polymorphism (rs2033529) were nominally associated with ΔEDSS. The constructed lipid CGRS showed a significant, dose-dependent association with ΔEDSS (p_trend=1.4×10^-6), such that participants having ≥6 risk alleles progressed 0.38 EDSS points per year faster compared with those having ≤3. This CGRS model explained 16% of the variance in ΔEDSS. We also found significant interactions between the CGRS and lipid levels in modulating ΔEDSS, including high-density lipoprotein (HDL; p_interaction=0.005) and total cholesterol:high-density lipoprotein ratio (TC:HDL; p_interaction=0.030). The combined model (combination of CGRS and the lipid parameter) explained 26% of the disability variance for HDL and 27% for TC:HDL.

INTERPRETATION

In this prospective cohort study, both lipid levels and lipid-related polymorphisms individually and jointly were associated with significantly increased disability progression in MS. These results indicate that these polymorphisms and tagged genes might be potential points of intervention to moderate disability progression.

A decade in psychiatric GWAS research

After more than 10 years of accumulated efforts, genome-wide association studies (GWAS) have led to many findings, most of which have been deposited into the GWAS Catalog. Between GWAS's inception and March 2017, the GWAS Catalog has collected 2429 studies, 1818 phenotypes, and 28,462 associated SNPs. We reclassified the psychology-related phenotypes into 217 reclassified phenotypes, which accounted for 514 studies and 7052 SNPs. In total, 1223 of the SNPs reached genome-wide significance. Of these, 147 were replicated for the same psychological trait in different studies. Another 305 SNPs were replicated within one original study. The SNPs rs2075650 and rs4420638 were linked to the most replications within a single reclassified phenotype or very similar reclassified phenotypes; both were associated with Alzheimer's disease (AD). Schizophrenia was associated with 74 within-phenotype SNPs reported in independents studies. Alzheimer's disease and schizophrenia were both linked to some physical phenotypes, including cholesterol and body mass index, through common GWAS signals. Alzheimer's disease also shared risk SNPs with age-related phenotypes such as age-related macular degeneration and longevity. Smoking-related SNPs were linked to lung cancer and respiratory function. Alcohol-related SNPs were associated with cardiovascular and digestive system phenotypes and disorders. Two separate studies also identified a shared risk SNP for bipolar disorder and educational attainment. This review revealed a list of reproducible SNPs worthy of future functional investigation. Additionally, by identifying SNPs associated with multiple phenotypes, we illustrated the importance of studying the relationships among phenotypes to resolve the nature of their causal links. The insights within this review will hopefully pave the way for future evidence-based genetic studies.

Generalizability and applicability of results obtained from populations of European descent regarding the effect direction and size of HDL-C level-associated genetic variants to the Hungarian general and Roma populations

OBJECTIVES

Large-scale association studies that mainly involve European populations identified many genetic loci related to high-density lipoprotein cholesterol (HDL-C) levels, one of the most important indicators of the risk for cardiovascular diseases. The question with intense speculation of whether the effect estimates obtained from European populations for different HDL-C level-related SNPs are applicable to the Roma ethnicity, the largest minority group in Europe with a South Asian origin, was addressed in the present study.

DESIGN

The associations between 21 SNPs (in the genes LIPC(G), CETP, GALNT2, HMGCP, ABCA1, KCTD10 and WWOX) and HDL-C levels were examined separately in adults of the Hungarian general (N = 1542) and Roma (N = 646) populations by linear regression. Individual effects (direction and size) of single SNPs on HDL-C levels were computed and compared between the study groups and with data published in the literature.

RESULTS

Significant associations between SNPs and HDL-C levels were more frequently found in general subjects than in Roma subjects (11 SNPs in general vs. 4 SNPs in Roma). The CETP gene variants rs1532624, rs708272 and rs7499892 consistently showed significant associations with HDL-C levels across the study groups (p ˂ 0.05), indicating a possible causal variant(s) in this region. Although nominally significant differences in effect size were found for three SNPs (rs693 in gene APOB, rs9989419 in gene CETP, and rs2548861 in gene WWOX) by comparing the general and Roma populations, most of these SNPs did not have a significant effect on HDL-C levels. The β coefficients for SNPs in the Roma population were found to be identical both in direction and magnitude to the effect obtained previously in large-scale studies on European populations.

CONCLUSIONS

The effect of the vast majority of the SNPs on HDL-C levels could be replicated in the Hungarian general and Roma populations, which indicates that the effect size measurements obtained from the literature can be used for risk estimation for both populations.

The role of genetic variation of human metabolism for BMI, mental traits and mental disorders

OBJECTIVE

The aim was to assess whether loci associated with metabolic traits also have a significant role in BMI and mental traits/disorders METHODS: We first assessed the number of single nucleotide polymorphisms (SNPs) with genome-wide significance for human metabolism (NHGRI-EBI Catalog). These 516 SNPs (216 independent loci) were looked-up in genome-wide association studies for association with body mass index (BMI) and the mental traits/disorders educational attainment, neuroticism, schizophrenia, well-being, anxiety, depressive symptoms, major depressive disorder, autism-spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer's disease, bipolar disorder, aggressive behavior, and internalizing problems. A strict significance threshold of p < 6.92 × 10-6 was based on the correction for 516 SNPs and all 14 phenotypes, a second less conservative threshold (p < 9.69 × 10-5) on the correction for the 516 SNPs only.

RESULTS

19 SNPs located in nine independent loci revealed p-values < 6.92 × 10-6; the less strict criterion was met by 41 SNPs in 24 independent loci. BMI and schizophrenia showed the most pronounced genetic overlap with human metabolism with three loci each meeting the strict significance threshold. Overall, genetic variation associated with estimated glomerular filtration rate showed up frequently; single metabolite SNPs were associated with more than one phenotype. Replications in independent samples were obtained for BMI and educational attainment.

CONCLUSIONS

Approximately 5-10% of the regions involved in the regulation of blood/urine metabolite levels seem to also play a role in BMI and mental traits/disorders and related phenotypes. If validated in metabolomic studies of the respective phenotypes, the associated blood/urine metabolites may enable novel preventive and therapeutic strategies.

A large electronic-health-record-based genome-wide study of serum lipids

A genome-wide association study of 94,674 multi-ethnic Kaiser Permanente members utilizing 478,866 longitudinal untreated serum lipid electronic-health-record-derived measurements (EHRs) empowered multiple novel findings: 121 new SNP associations (46 primary, 15 conditional, 60 in meta-analysis with Global Lipids Genetic Consortium); increase of 33-42% in variance explained with multiple measurements; sex differences in genetic impact (greater in females for LDL, HDL, TC, the opposite for TG); differences in variance explained amongst non-Hispanic whites, Latinos, African Americans, and East Asians; genetic dominance and epistasis, with strong evidence for both at ABOxFUT2 for LDL; and eQTL tissue-enrichment implicating the liver, adipose, and pancreas. Utilizing EHR pharmacy data, both LDL and TG genetic risk scores (477 SNPs) were strongly predictive of age-at-initiation of lipid-lowering treatment. These findings highlight the value of longitudinal EHRs for identifying novel genetic features of cholesterol and lipoprotein metabolism with implications for lipid treatment and risk of coronary heart disease.

Association of common variants in TOMM40/APOE/APOC1 region with human longevity in a Chinese population

Apolipoprotein E (APOE), translocase of outer mitochondrial membrane 40 homolog (TOMM40) and apolipoprotein C-I (APOC1) may extend lifespan by marked delay or escape from age-related diseases. This study aimed to elucidate the association of human longevity with genetic variations in TOMM40/APOE/APOC1 region in a Chinese population. Ten tag single-nucleotide polymorphisms (SNPs) in the TOMM40/APOE/APOC1 region were successfully genotyped in 616 unrelated long-lived individuals and 846 younger controls. Of the 10 SNPs, rs7254892 in 5' upstream of TOMM40 showed significant association with human longevity (G/A-A/A vs G/G: odds ratio (OR)=1.59, 95% confidence interval (CI)=1.20-2.09, P=0.0011, Bonferroni corrected P (Pc)=0.033). The haplotype analysis suggested that individuals carrying the haplotype A-A-A-A-T-A-T-G-C-A (rs7254892-rs157580-rs2075649-rs2075650-rs157582-rs8106922-rs1160985-rs405697-rs439401-rs445925) tended to have longer lifespan than those carrying the most common haplotype G-G-A-A-C-A-C-A-T-G (OR=1.59, 95% CI=1.19-2.12, P=0.0018, Pc=0.0216). These findings indicated that variants in TOMM40/APOE/APOC1 region might be associated with human longevity. Further studies are needed to identify the causal genetic variants influencing human longevity.

Genetic variants in AKR1B10 associate with human eating behavior

BACKGROUND

The human Aldoketoreductase 1B10 gene (AKR1B10) encodes one of the enzymes belonging to the family of aldoketoreductases and may be involved in detoxification of nutrients during digestion. Further, AKR1B10 mRNA (messenger ribonucleic acid) expression was diminished in brain regions potentially involved in the regulation of eating behavior in rats which are more sensitive to cocaine and alcohol. We hypothesized that the human AKR1B10 gene may also play a role in the regulation of human eating behavior.

RESULTS

We investigated the effects of 5 genetic variants of AKR1B10 on human eating behavior among 548 subjects from a German self-contained population, the Sorbs, and in 350 subjects from another independent German cohort. Among the Sorbs, we observed nominal associations with disinhibition at the 5' untranslated region (5' UTR) variant rs10232478 and the intragenic variants rs1834150 and rs782881 (all P ≤ 0.05). Further, we detected a relationship of rs1834150 and rs782881 with waist, smoking consumption (rs782881) and coffee consumption (rs1834150) (all P ≤ 0.05). Albeit non-significant, replication analyses revealed similar effect directions for disinhibition at rs1834150 (combined P = 0.0096). Moreover, in the replication cohort we found rs1834150 related to increased restraint scores with a similar direction as in the Sorbs (combined P = 0.0072).

CONCLUSION

Our data suggest that genetic variants in the AKR1B10 locus may influence human eating behavior.