Human Heredity最新文献

Introduction: Liver disease accounts for approximately 2 million deaths per year worldwide. The majority of liver diseases are due to complications of cirrhosis, viral hepatitis, and hepatocellular carcinoma. Increased levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) may indicate liver disease. Moreover, there are additional noninvasive liver fibrosis indices that help to estimate liver damage, including AST-to-ALT ratio, AST-to-platelet ratio index (APRI), fibrosis-4 (FIB-4) score, and nonalcoholic fatty liver disease (NAFLD) fibrosis score. The aims of the present study were to (1) perform an association analysis of the patatin-like phospholipase domain containing 3 (PNPLA3) I148M (rs738409) variant with ALT, AST, and various liver fibrosis indices, and (2) determine whether there are gender-related differences in these associations.

Methods: We obtained demographic, anthropometric, and metabolic phenotypes from Latino adult participants (n = 503, 64% female, 36.4 ± 0.5 years) from the Arizona Insulin Resistance (AIR) registry. SNP genotyping of I148M was performed using the TaqMan allelic discrimination assay. We used linear regression for the association analyses of the genotypes with ALT, AST, and the various liver fibrosis indices. We included genotype, age, body mass index, and alcohol status in the linear regression model.

Results: The variant I148M was in Hardy-Weinberg equilibrium, with genotype distribution: non-risk CC 118, heterozygous CG 246, and risk GG 139. The G allele was significantly associated with increased ALT and AST levels (p = 7.8 × 10-7 and p = 9.7 × 10-6, respectively). Moreover, we showed that the G allele was significantly associated with higher APRI (p = 3.7 × 10-7) and FIB-4 score (p = 4.1 × 10-3). When we analyzed the data by gender, we observed similar significant trends for ALT, AST, and APRI (all, p < 0.01). In females, the G allele was significantly associated with increased FIB-4 score (p = 6.9 × 10-3), which was not observed in the males (p > 0.05). There was no association of the I148M variant with AST/ALT ratio nor NAFLD risk score, whether analyzed in all adults or by gender.

Discussion/conclusion: Our findings provide additional evidence of an association of PNPLA3 I148M with several liver disease biomarkers in male and female Latinos residing in the Southwest of the United States.

Objectives: Peripheral blood mononuclear cells (PBMCs) are critical for immunity and participate in multiple human diseases, including rheumatoid arthritis (RA). PhosSNPs are nonsynonymous SNPs influencing protein phosphorylation, thus probably modulate cell signaling and gene expression. We aimed to identify phosSNPs-regulated gene network/pathway potentially significant for RA.

Methods: We collected genome-wide phosSNP genotyping data and transcriptome-wide mRNA expression data from PBMCs of a Chinese sample. We discovered and verified with public datasets differentially expressed genes (DEGs) associated with RA, and replicated RA-associated SNPs in our study sample. We performed a targeted expression quantitative trait locus (eQTL) study on significant phosSNPs and DEGs.

Results: We identified 29 nominally significant eQTL phosSNPs and 83 target genes, and constructed comprehensive regulatory/interaction networks, highlighting the vital effects of two eQTL phosSNPs (rs371513 and rs4824675, FDR <0.05) and four critical node genes (HSPA4, NDUFA2, MRPL15, and ATP5O). Besides, two node/key genes NDUFA2 and ATP5O, regulated by rs371513, were significantly enriched in mitochondrial oxidative phosphorylation pathway. Besides, four pairs of eQTL effects were replicated independently in whole blood and/or transformed fibroblasts.

Conclusions: The findings delineated a potential role of protein phosphorylation and genetic variations in RA and warranted the significant roles of phosSNPs in regulating RA-associated genes expression in PBMCs. The results pointed out the relevance and significance of oxidative phosphorylation pathway to RA.

Multiple familial diseases in a single patient often present with overlapping symptomatology that confers difficulty in delineating a clinical diagnosis. Pedigree analysis has been a long-standing practice in the field of medical genetics to discover familial diseases. In recent years, whole exome sequencing (WES) has proven to be a useful tool for aiding physicians in diagnosing and understanding disease etiology. This report shows that pedigree analysis and WES are co-dependent processes in establishing diagnoses in a family with 4 different genetic disorders: Birt-Hogg-Dubé Syndrome, RRM2B-related mitochondrial disease, CDC73-related primary hyperparathyroidism, and familial prostate cancer.

Many complex diseases are caused by single nucleotide polymorphisms (SNPs), environmental factors, and the interaction between SNPs and environment. Joint tests of the SNP and SNP-environment interaction effects (JMA) and meta-regression (MR) are commonly used to evaluate these SNP-environment interactions. However, these two methods do not consider genetic heterogeneity. We previously presented a random-effect MR, which provided higher power than the MR in datasets with high heterogeneity. However, this method requires group-level data, which sometimes are not available. Given this, we designed this study to evaluate the introduction of the random effects of SNP and SNP-environment interaction into the JMA, and then extended this to the random effect model. Likelihood ratio statistic is applied to test the JMA and the new method we proposed in this paper. We evaluated the null distributions of these tests, and the powers for this method. This method was verified by simulation and was shown to provide similar powers to the random effect meta-regression method (RMR). However, this method only requires study-level data which relaxed the condition of the RMR. Our study suggests that this method is more suitable for finding the association between SNP and diseases in the absence of group-level data.

Background: Many cancer types show considerable heritability, and extensive research has been done to identify germline susceptibility variants. Linkage studies have discovered many rare high-risk variants, and genome-wide association studies (GWAS) have discovered many common low-risk variants. However, it is believed that a considerable proportion of the heritability of cancer remains unexplained by known susceptibility variants. The "rare variant hypothesis" proposes that much of the missing heritability lies in rare variants that cannot reliably be detected by linkage analysis or GWAS. Until recently, high sequencing costs have precluded extensive surveys of rare variants, but technological advances have now made it possible to analyze rare variants on a much greater scale.

Objectives: In this study, we investigated associations between rare variants and 14 cancer types.

Methods: We ran association tests using whole-exome sequencing data from The Cancer Genome Atlas (TCGA) and validated the findings using data from the Pan-Cancer Analysis of Whole Genomes Consortium (PCAWG).

Results: We identified four significant associations in TCGA, only one of which was replicated in PCAWG (BRCA1 and ovarian cancer).

Conclusions: Our results provide little evidence in favor of the rare variant hypothesis. Much larger sample sizes may be needed to detect undiscovered rare cancer variants.