Genetic variants in the CPNE5 gene are associated with alcohol dependence and obesity in Caucasian populations

Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI

There is inconsistent evidence for an association of obesity with white matter microstructural alterations. Such inconsistent findings may be related to the cumulative effects of obesity and alcohol dependence. This study aimed to investigate the possible interactions between alcohol dependence and overweight/obesity on white matter microstructure in the human brain. A total of 60 inpatients with alcohol dependence during early abstinence (44 normal weight and 16 overweight/obese) and 65 controls (42 normal weight and 23 overweight/obese) were included. The diffusion tensor imaging (DTI) measures [fractional anisotropy (FA) and radial diffusivity (RD)] of the white matter microstructure were compared between groups. We observed significant interactive effects between alcohol dependence and overweight/obesity on DTI measures in several tracts. The DTI measures were not significantly different between the overweight/obese and normal-weight groups (although widespread trends of increased FA and decreased RD were observed) among controls. However, among the alcohol-dependent patients, the overweight/obese group had widespread reductions in FA and widespread increases in RD, most of which significantly differed from the normal-weight group; among those with overweight/obesity, the alcohol-dependent group had widespread reductions in FA and widespread increases in RD, most of which were significantly different from the control group. This study found significant interactive effects between overweight/obesity and alcohol dependence on white matter microstructure, indicating that these two controllable factors may synergistically impact white matter microstructure and disrupt structural connectivity in the human brain.

Copine7 deficiency leads to hepatic fat accumulation via mitochondrial dysfunction

Objective

Mitochondrial dysfunction affects hepatic lipid homeostasis and promotes ROS generation. Copine7 (CPNE7) belongs to the ubiquitous copine family of calcium-dependent phospholipid binding proteins. CPNE7 has a high calcium ion binding affinity and the capacity to scavenge reactive oxygen species (ROS). A recent study reported that abnormalities in fatty acid and lipid metabolism were linked to the gene variant of CPNE7. Therefore, the purpose of this study is to examine the role of Cpne7 in hepatic lipid metabolism based on mitochondrial function.

Methods

Lipid metabolism, mitochondrial function, and ROS production were investigated in high-fat diet (HFD)-fed Cpne7-/- mice and H2O2-damaged HepG2 hepatocytes following CPNE7 silencing or overexpression.

Results

Cpne7 deficiency promoted severe hepatic steatosis in the HFD-induced NAFLD model. More importantly, mitochondrial dysfunction was observed along with an imbalance of mitochondrial dynamics in the livers of HFD-fed Cpne7-/-mice, resulting in high ROS levels. Similarly, CPNE7-silenced HepG2 hepatocytes showed high ROS levels, mitochondrial dysfunction, and increased lipid contents. On the contrary, CPNE7-overexpressed HepG2 cells showed low ROS levels, enhanced mitochondrial function and decreased lipid contents under H2O2-induced oxidative stress.

Conclusions

In the liver, Cpne7 deficiency causes excessive ROS formation and mitochondrial dysfunction, which aggravates lipid metabolism abnormalities. These findings provide evidence that Cpne7 deficiency contributes to the pathogenesis of NAFLD, suggesting Cpne7 as a novel therapeutic target for NAFLD.

Advances in sports genomics

Sports genomics is the scientific discipline that focuses on the organization and function of the genome in elite athletes, and aims to develop molecular methods for talent identification, personalized exercise training, nutritional need and prevention of exercise-related diseases. It postulates that both genetic and environmental factors play a key role in athletic performance and related phenotypes. This update on the panel of genetic markers (DNA polymorphisms) associated with athlete status and soft-tissue injuries covers advances in research reported in recent years, including one whole genome sequencing (WGS) and four genome-wide association (GWAS) studies, as well as findings from collaborative projects and meta-analyses. At end of 2020, the total number of DNA polymorphisms associated with athlete status was 220, of which 97 markers have been found significant in at least two studies (35 endurance-related, 24 power-related, and 38 strength-related). Furthermore, 29 genetic markers have been linked to soft-tissue injuries in at least two studies. The most promising genetic markers include HFE rs1799945, MYBPC3 rs1052373, NFIA-AS2 rs1572312, PPARA rs4253778, and PPARGC1A rs8192678 for endurance; ACTN3 rs1815739, AMPD1 rs17602729, CPNE5 rs3213537, CKM rs8111989, and NOS3 rs2070744 for power; LRPPRC rs10186876, MMS22L rs9320823, PHACTR1 rs6905419, and PPARG rs1801282 for strength; and COL1A1 rs1800012, COL5A1 rs12722, COL12A1 rs970547, MMP1 rs1799750, MMP3 rs679620, and TIMP2 rs4789932 for soft-tissue injuries. It should be appreciated, however, that hundreds and even thousands of DNA polymorphisms are needed for the prediction of athletic performance and injury risk.

Alcohol drinking in one's thirties and forties is associated with body mass index in men, but not in women: A longitudinal analysis of the 1970 British Cohort Study

Our objective was to investigate longitudinal associations between alcohol drinking and body mass index (BMI). Alcohol drinking (exposure), BMI (outcome), smoking habit, occupation, longstanding illness, and leisure time physical activity (potential confounders) were assessed at ages 30, 34, 42, and 46 in the 1970 British Birth Cohort Study. Multilevel models were used to cope with the problem of correlated observations. There were 15,708 observations in 5931 men and 14,077 observations in 5656 women. Drinking was associated with BMI in men. According to the regression coefficients, BMI was expected to increase by 0.36 (95% confidence interval: 0.11, 0.60) kg/m² per year in men who drank once a week and by 0.40 (0.14, 0.15) kg/m² per year in men who drank most days. In ten years, BMI was expected to increase by 5.4 kg/m² in men who drank and by 2.9 kg/m² in men who drank and were physically active. Drinking was not associated with BMI in women. Rather, BMI was expected to increase by 0.25 (0.07, 0.43) kg/m² per year in women who were former smokers. In ten years, BMI was expected to increase by 4.3 kg/m² in women who were former smokers and by 0.8 kg/m² in women who were former smokers and who were physically active. Associations between drinking and BMI were similar after further adjustment for problematic drinking and diet. These longitudinal data suggest that drinking is associated with BMI in men and that drinking is not associated with BMI in women independent of other lifestyle risk factors.

An imputed whole-genome sequence-based GWAS approach pinpoints causal mutations for complex traits in a specific swine population

Sequencing-based genome-wide association studies (GWAS) have facilitated the identification of causal associations between genetic variants and traits in diverse species. However, it is cost-prohibitive for the majority of research groups to sequence a large number of samples. Here, we carried out genotype imputation to increase the density of single nucleotide polymorphisms in a large-scale Swine F₂ population using a reference panel including 117 individuals, followed by a series of GWAS analyses. The imputation accuracies reached 0.89 and 0.86 for allelic concordance and correlation, respectively. A quantitative trait nucleotide (QTN) affecting the chest vertebrate was detected directly, while the investigation of another QTN affecting the residual glucose failed due to the presence of similar haplotypes carrying wild-type and mutant allelesin the reference panel used in this study. A high imputation accuracy was confirmed by Sanger sequencing technology for the most significant loci. Two candidate genes, CPNE5 and MYH3, affecting meat-related traits were proposed. Collectively, we illustrated four scenarios in imputation-based GWAS that may be encountered by researchers, and our results will provide an extensive reference for future genotype imputation-based GWAS analyses in the future.

High expression of CPNE5 and CPNE9 predicts positive prognosis in multiple myeloma

BACKGROUND

CPNEs are significant biomarkers which can affect the progression and prognosis of various tumor diseases. However, the prognosis role of CPNEs in multiple myeloma (MM) is still unclear.

OBJECTIVES

To investigate the prognosis role of CPNEs in MM.

METHODS

Seven hundred and thirty-five samples from two independent data sets were involved to analyze the clinical and molecular characteristics, and prognosis role of the expression of CPNE1-9 in MM.

RESULTS

MM patients with higher expressions of CPNE5 and CPNE9 had longer event-free survival (EFS) and overall survival (OS) compared with CPNE5low and CPNE9low expression groups (EFS: P= 0.0054, 0.0065; OS: P= 0.015, 0.016, respectively). Multivariate regression analysis showed that CPNE5 was an independent favorable predictor for EFS and OS (EFS: P= 0.005; OS: P= 0.006), and CPNE9 was an independent positive indicator for EFS (P= 0.002). Moreover, the survival probability and the cumulative event of EFS and OS in CPNE5highCPNE9high group were significantly longer than other groups.

CONCLUSIONS

High expressions of CPNE5 and CPNE9 might be used as positive indicators for MM, and their combination was a better predictor for the survival of MM patients.

Are Genome-Wide Association Study Identified Single-Nucleotide Polymorphisms Associated With Sprint Athletic Status? A Replication Study With 3 Different Cohorts

PURPOSE

To replicate previous genome-wide association study identified sprint-related polymorphisms in 3 different cohorts of top-level sprinters and to further validate the obtained results in functional studies.

METHODS

A total of 240 Japanese, 290 Russians, and 593 Brazilians were evaluated in a case-control approach. Of these, 267 were top-level sprint/power athletes. In addition, the relationship between selected polymorphisms and muscle fiber composition was evaluated in 203 Japanese and 287 Finnish individuals.

RESULTS

The G allele of the rs3213537 polymorphism was overrepresented in Japanese (odds ratio [OR]: 2.07, P = .024) and Russian (OR: 1.93, P = .027) sprinters compared with endurance athletes and was associated with an increased proportion of fast-twitch muscle fibers in Japanese (P = .02) and Finnish (P = .041) individuals. A meta-analysis of the data from 4 athlete cohorts confirmed that the presence of the G/G genotype rather than the G/A+A/A genotypes increased the OR of being a sprinter compared with controls (OR: 1.49, P = .01), endurance athletes (OR: 1.79, P = .001), or controls + endurance athletes (OR: 1.58, P = .002). Furthermore, male sprinters with the G/G genotype were found to have significantly faster personal times in the 100-m dash than those with G/A+A/A genotypes (10.50 [0.26] vs 10.76 [0.31], P = .014).

CONCLUSION

The rs3213537 polymorphism found in the CPNE5 gene was identified as a highly replicable variant associated with sprinting ability and the increased proportion of fast-twitch muscle fibers, in which the homozygous genotype for the major allele (ie, the G/G genotype) is preferable for performance.

Dietary yeast influences ethanol sedation in Drosophila via serotonergic neuron function

Abuse of alcohol is a major clinical problem with far-reaching health consequences. Understanding the environmental and genetic factors that contribute to alcohol-related behaviors is a potential gateway for developing novel therapeutic approaches for patients that abuse the drug. To this end, we have used Drosophila melanogaster as a model to investigate the effect of diet, an environmental factor, on ethanol sedation. Providing flies with diets high in yeast, a routinely used component of fly media, increased their resistance to ethanol sedation. The yeast-induced resistance to ethanol sedation occurred in several different genetic backgrounds, was observed in males and females, was elicited by yeast from different sources, was readily reversible, and was associated with increased nutrient intake as well as decreased internal ethanol levels. Inhibition of serotonergic neuron function using multiple independent genetic manipulations blocked the effect of yeast supplementation on ethanol sedation, nutrient intake, and internal ethanol levels. Our results demonstrate that yeast is a critical dietary component that influences ethanol sedation in flies and that serotonergic signaling is required for the effect of dietary yeast on nutrient intake, ethanol uptake/elimination, and ethanol sedation. Our studies establish the fly as a model for diet-induced changes in ethanol sedation and raise the possibility that serotonin might mediate the effect of diet on alcohol-related behavior in other species.

Genetic architecture and adaptations of Nunavik Inuit

The Canadian Inuit have a distinct population background that may entail particular implications for the health of its individuals. However, the number of genetic studies examining this Inuit population is limited, and much remains to be discovered in regard to its genetic characteristics. In this study, we generated whole-exome sequences and genomewide genotypes for 170 Nunavik Inuit, a small and isolated founder population of Canadian Arctic indigenous people. Our study revealed the genetic background of Nunavik Inuit to be distinct from any known present-day population. The majority of Nunavik Inuit show little evidence of gene flow from European or present-day Native American peoples, and Inuit living around Hudson Bay are genetically distinct from those around Ungava Bay. We also inferred that Nunavik Inuit have a small effective population size of 3,000 and likely split from Greenlandic Inuit ∼10.5 kya. Nunavik Inuit went through a bottleneck at approximately the same time and might have admixed with a population related to the Paleo-Eskimos. Our study highlights population-specific genomic signatures in coding regions that show adaptations unique to Nunavik Inuit, particularly in pathways involving fatty acid metabolism and cellular adhesion (CPNE7, ICAM5, STAT2, and RAF1). Subsequent analyses in selection footprints and the risk of intracranial aneurysms (IAs) in Nunavik Inuit revealed an exonic variant under weak negative selection to be significantly associated with IA (rs77470587; P = 4.6 × 10^-8).

HisCoM-GGI: Hierarchical structural component analysis of gene-gene interactions

Although genome-wide association studies (GWAS) have successfully identified thousands of single nucleotide polymorphisms (SNPs) associated with common diseases, these observations are limited for fully explaining "missing heritability". Determining gene-gene interactions (GGI) are one possible avenue for addressing the missing heritability problem. While many statistical approaches have been proposed to detect GGI, most of these focus primarily on SNP-to-SNP interactions. While there are many advantages of gene-based GGI analyses, such as reducing the burden of multiple-testing correction, and increasing power by aggregating multiple causal signals across SNPs in specific genes, only a few methods are available. In this study, we proposed a new statistical approach for gene-based GGI analysis, "Hierarchical structural CoMponent analysis of Gene-Gene Interactions" (HisCoM-GGI). HisCoM-GGI is based on generalized structured component analysis, and can consider hierarchical structural relationships between genes and SNPs. For a pair of genes, HisCoM-GGI first effectively summarizes all possible pairwise SNP-SNP interactions into a latent variable, from which it then performs GGI analysis. HisCoM-GGI can evaluate both gene-level and SNP-level interactions. Through simulation studies, HisCoM-GGI demonstrated higher statistical power than existing gene-based GGI methods, in analyzing a GWAS of a Korean population for identifying GGI associated with body mass index. Resultantly, HisCoM-GGI successfully identified 14 potential GGI, two of which, (NCOR2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>×</mml:mo></mml:math> SPOCK1) and (LINGO2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>×</mml:mo></mml:math> ZNF385D) were successfully replicated in independent datasets. We conclude that HisCoM-GGI method may be a valuable tool for genome to identify GGI in missing heritability, allowing us to better understand the biological genetic mechanisms of complex traits. We conclude that HisCoM-GGI method may be a valuable tool for genome to identify GGI in missing heritability, allowing us to better understand biological genetic mechanisms of complex traits. An implementation of HisCoM-GGI can be downloaded from the website ( http://statgen.snu.ac.kr/software/hiscom-ggi ).

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI

Background

The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins.

Results

In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly correlated with BMI (r = 0.56, P = 0.04), and hub genes of KCNN1 and AQP10 were differentially expressed.

Conclusion

We identified significant genes and specific modules potentially related to BMI based on the gene expression profile data of monozygotic twins. The findings may help further elucidate the underlying mechanisms of obesity development and provide novel insights to research potential gene biomarkers and signaling pathways for obesity treatment. Further analysis and validation of the findings reported here are important and necessary when more sample size is acquired.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4257-6) contains supplementary material, which is available to authorized users.

Stratified polygenic risk prediction model with application to CAGI bipolar disorder sequencing data

Genetic data consists of a wide range of marker types, including common, low-frequency, and rare variants. Multiple genetic markers and their interactions play central roles in the heritability of complex disease. In this study, we propose an algorithm that uses a stratified variable selection design by genetic architectures and interaction effects, achieved by a dataset-adaptive W-test. The polygenic sets in all strata were integrated to form a classification rule. The algorithm was applied to the Critical Assessment of Genome Interpretation 4 bipolar challenge sequencing data. The prediction accuracy was 60% using genetic markers on an independent test set. We found that epistasis among common genetic variants contributed most substantially to prediction precision. However, the sample size was not large enough to draw conclusions for the lack of predictability of low-frequency variants and their epistasis.

Impaired learning and memory in rats induced by a high-fat diet: Involvement with the imbalance of nesfatin-1 abundance and copine 6 expression

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, resulting not only in liver dysfunction, glucose and lipid metabolism disorder, but also in neuropsychiatric damage. In the present study, a NAFLD rat model was established via feeding of a high-fat diet, and behaviour was observed via the open field test (OFT), the sucrose preference test (SPT), the elevated plus maze (EPM), the forced swimming test (FST) and the Morris water maze (MWM). The plasma concentrations of alanine aminotransferase (ALT), glucose, free fatty acid (FFA), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were detected using chemiluminescence technique. The plasma levels of nesfatin-1, leptin and insulin were measured via enzyme-linked immunosorbent assay, and the protein expressions of p-glycogen synthase kinase-3β (GSK-3β), GSK-3β, p-β-catenin, β-catenin, cyclinD and copine 6 in the hippocampus and prefrontal cortex (PFC) were detected using western blotting. After 4 consecutive weeks of feeding with a high-fat diet, the rats showed obesity; increased plasma concentrations of ALT, glucose, FFA, TC, TG, HDL-C and LDL-C; decreased plasma levels of leptin and insulin; and inflammation and mild hepatocyte steatosis in the liver. Although there was no significant difference between groups with regard to performance in the OFT, EPM or FST, the NAFLD rats showed a decreased sucrose preference index in the SPT and impaired learning and memory in the MWM task. Moreover, the present study provides the first evidence of an increased plasma nesfatin-1 concentration in NAFLD rats, which was significantly correlated with plasma lipid concentrations and behavioural performance. Furthermore, copine 6 and p-β-catenin protein expression decreased and p-GSK-3β increased in the hippocampus and PFC of NAFLD rats. These results suggest that consuming of a high-fat diet for 4 consecutive weeks could successfully induce a NAFLD rat model. More importantly, these results provide the first evidence that impaired learning and memory in NAFLD rats was, at least partly, associated with increased plasma nesfatin-1 concentration and decreased copine 6 expression in the hippocampus and PFC.

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors

The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors.