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Genetic risk factors for hypertension may have age or gender specificity and pleiotropic effects. This study aims to measure the risk of genetic and non-genetic factors in the occurrence of hypertension and related diseases, with consideration of potential confounding factors and age-gender stratification. A discovery set of 352,228 genotyped plus 1.8 million imputed single-nucleotide polymorphisms were analyzed for 2,886 hypertensive cases and 3,440 healthy controls obtained from two community-based cohorts in Korea, and selected gene variants were replicated in the Health Examinee cohort (665 cases and 1,285 controls). Genome-wide association analyses were conducted in 12 groups stratified by age and gender after adjusting for potential covariates under three genetic models. Age, rural area residence, body mass index, family history of hypertension, male gender, current alcohol drinking status, and current smoking status were significantly associated with hypertension (P = 4 × 10(-151) to 0.011). Five gene variants, rs11066280 (C12orf51), rs12229654 and rs3782889 (MYL2), rs2072134 (OAS3), rs2093395 (TREML2), and rs17249754 (ATP2B1), were found to be associated with hypertension mostly in men (P = 4.76 × 10(-14) to 4.46 × 10(-7) in the joint analysis); three SNPs (rs11066280, rs12229654, and rs3782889) remained significant after Bonferroni correction in an independent population. Three gene variants, rs12229654, rs17249754, and rs11066280, were significantly associated with metabolic disorders such as hyperlipidemia and diabetes (P = 0.00071 to 0.0097, respectively). Careful consideration of the potential confounding effects in future genome-wide association studies is necessary to uncover the genetic underpinnings of complex diseases.

While carotid intima-media thickness (cIMT) as a noninvasive surrogate measure of atherosclerosis is widely considered a risk factor for stroke, the intrinsic link underlying cIMT and stroke has not been fully understood. We aimed to evaluate the clinical value of cIMT in stroke through the investigation of phenotypic and genetic relationships between cIMT and stroke. We evaluated phenotypic associations using observational data from UK Biobank (N = 21,526). We then investigated genetic relationships leveraging genomic data conducted in predominantly European ancestry for cIMT (N = 45,185) and any stroke (AS, N case /N control =40,585/406,111). Observational analyses suggested an increased hazard of stroke per one standard deviation increase in cIMT (cIMT max -AS: hazard ratio (HR) = 1.39, 95%CI = 1.09-1.79; cIMT mean -AS: HR = 1.39, 95%CI = 1.09-1.78; cIMT min -AS: HR = 1.32, 95%CI = 1.04-1.68). A positive global genetic correlation was observed (cIMT max -AS: [Formula: see text]=0.23, P=9.44 × 10 -5 ; cIMT mean -AS: [Formula: see text]=0.21, P=3.00 × 10 -4 ; cIMT min -AS: [Formula: see text]=0.16, P=6.30 × 10 -3 ). This was further substantiated by five shared independent loci and 15 shared expression-trait associations. Mendelian randomization analyses suggested no causal effect of cIMT on stroke (cIMT max -AS: odds ratio (OR)=1.12, 95%CI=0.97-1.28; cIMT mean -AS: OR=1.09, 95%CI=0.93-1.26; cIMT min -AS: OR=1.03, 95%CI = 0.90-1.17). A putative association was observed for genetically predicted stroke on cIMT (AS-cIMT max : beta=0.07, 95%CI = 0.01-0.13; AS-cIMT mean : beta=0.08, 95%CI = 0.01-0.15; AS-cIMT min : beta = 0.08, 95%CI = 0.01-0.16) in the reverse direction MR, which attenuated to non-significant in sensitivity analysis. Our work does not find evidence supporting causal associations between cIMT and stroke. The pronounced cIMT-stroke association is intrinsic, and mostly attributed to shared genetic components. The clinical value of cIMT as a surrogate marker for stroke risk in the general population is likely limited., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Fatty acid elongase ELOVL5 is part of a protein family of multipass transmembrane proteins that reside in the endoplasmic reticulum where they regulate long-chain fatty acid elongation. A missense variant (c.689G>T p.Gly230Val) in ELOVL5 causes Spinocerebellar Ataxia subtype 38 (SCA38), a neurodegenerative disorder characterized by autosomal dominant inheritance, cerebellar Purkinje cell demise and adult-onset ataxia. Having previously showed aberrant accumulation of p.G230V in the Golgi complex, here we further investigated the pathogenic mechanisms triggered by p.G230V, integrating functional studies with bioinformatic analyses of protein sequence and structure. Biochemical analysis showed that p.G230V enzymatic activity was normal. In contrast, SCA38-derived fibroblasts showed reduced expression of ELOVL5, Golgi complex enlargement and increased proteasomal degradation with respect to controls. By heterologous overexpression, p.G230V was significantly more active than wild-type ELOVL5 in triggering the unfolded protein response and in decreasing viability in mouse cortical neurons. By homology modelling, we generated native and p.G230V protein structures whose superposition revealed a shift in Loop 6 in p.G230V that altered a highly conserved intramolecular disulphide bond. The conformation of this bond, connecting Loop 2 and Loop 6, appears to be elongase-specific. Alteration of this intramolecular interaction was also observed when comparing wild-type ELOVL4 and the p.W246G variant which causes SCA34. We demonstrate by sequence and structure analyses that ELOVL5 p.G230V and ELOVL4 p.W246G are position-equivalent missense variants. We conclude that SCA38 is a conformational disease and propose combined loss of function by mislocalization and gain of toxic function by ER/Golgi stress as early events in SCA38 pathogenesis. [ABSTRACT FROM AUTHOR]

About 10 years ago, after the first large-scale genome-wide association studies (GWAS) were conducted to find genes associated with common complex diseases, investigators were surprised to find that the amount of heritability explained by the significant hits was very low for almost all the studied traits. Indeed, when compared to heritability estimates expected from the observed trait concordance within families, the heritability explained by the associated variants was always much smaller, more than ten times smaller for some traits. There was thus a problem of "missing heritability" and different hypotheses were proposed to help find this "missing heritability". These hypotheses involved novel research strategies in which different groups engaged including among others increasing sample sizes of GWAS or looking for rare variants and structural variations that were not captured by the SNP-chips used in GWAS. How successful have these efforts been in finding the "missing heritability"? Could it be that the problem of "missing heritability" was ill-defined? These are the questions that will be addressed in this paper by taking some different examples of complex traits. [ABSTRACT FROM AUTHOR]

Several genome-wide association studies (GWAS) have identified genetic variants associated with birth weight. To date, however, most GWAS of birth weight have focused primarily on European ancestry samples even though prevalence of low birth weight is higher among African-Americans. We conducted admixture mapping using 2918 ancestral informative markers in 2596 participants of the Black Women’s Health Study, with the goal of identifying novel genomic regions where local African ancestry is associated with birth weight. In addition, we performed a replication analysis of 11 previously identified index single nucleotide polymorphisms (SNPs), and fine-mapped those genetic loci to identify better or new genetic variants associated with birth weight in African-Americans. We found that high African ancestry at 12q14 was associated with low birth weight, and we identified multiple independent birth weight-lowering variants in this genomic region. We replicated the association of a previous GWAS SNP in ADRB1 and our fine-mapping efforts suggested the presence of new birth weight-associated variants in ADRB1, HMGA2, and SLC2A4. Further studies are needed to determine whether birth weight-associated loci can in part explain race-associated birth weight disparities. [ABSTRACT FROM AUTHOR]

Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70 kg/m) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants. [ABSTRACT FROM AUTHOR]

Genetic variants with extreme allele frequency differences (EAFD) may underlie some human health disparities across populations. To identify EAFD loci, we systematically analyzed and characterized 81 million genomic variants from 2504 unrelated individuals of 26 world populations (phase III of the 1000 Genomes Project). Our analyses revealed a total of 434 genes, 15 pathways, and 18 diseases and traits influenced by EAFD variants from five continental populations. They included known EAFD genes, such as LCT (lactose tolerance), SLC24A5 (skin pigmentation), and EDAR (hair morphology). We found many novel EAFD genes, including TBC1D2B (autophagy mediator), TRIM40 (gastrointestinal inflammatory regulator), KRT71, KRT75, KRT83, and KRTAP10- 1 (hair and epithelial keratin synthesis), PIK3R3 (insulin receptor interaction), DARS (neurological disorders), and NACA2 (skin inflammatory response). Our results also showed four complex diseases significantly associated with EAFD loci, including asthma (adjusted enrichment P = 4 × 10), type I diabetes ( P = 6 × 10), alcohol consumption ( P = 0.0002), and attention deficit/hyperactivity disorder ( P = 0.003). This study provides a comprehensive atlas of genes, pathways, and human diseases significantly influenced by EAFD variants. [ABSTRACT FROM AUTHOR]

Genome-wide expressio n quantitative trait locus (eQTL) mapping may reveal common genetic variants regulating gene expression. In addition to mapping eQTLs, we systematically evaluated the heritability of the whole blood transcriptome in 5,626 participants from the Framingham Heart Study. Of all gene expression measurements, about 40 % exhibit evidence of being heritable [ $$h_{\text{geneExp}}^{ 2}$$ > 0, ( p < 0.05)], the average heritability was estimated to be 0.13, and 10 % display $$h_{\text{geneExp}}^{ 2}$$ > 0.2. To identify the role of eQTLs in promoting phenotype differences and disease susceptibility, we investigated the proportion of cis/ trans eQTLs in different heritability categories and discovered that genes with higher heritability are more likely to have cis eQTLs that explain large proportions of variance in the expression of the corresponding genes. Single cis eQTLs explain 0.33-0.53 of variance in transcripts on average, whereas single trans eQTLs only explain 0.02-0.07. The top cis eQTLs tend to explain more variance in the corresponding gene when its $$h_{\text{geneExp}}^{ 2}$$ is greater. Taking body mass index (BMI) as a case study, we cross-linked cis/ trans eQTLs with both GWAS SNPs and differentially expressed genes for BMI. We discovered that BMI GWAS SNPs in 16p11.2 (e.g., rs7359397) are associated with several BMI differentially expressed genes in a cis manner (e.g. SULT1A1, SPNS1, and TUFM). These BMI signature genes explain a much larger proportion of variance in BMI than do the GWAS SNPs. Our results shed light on the impact of eQTLs on the heritability of the human whole blood transcriptome and its relations to phenotype differences. [ABSTRACT FROM AUTHOR]

Epistasis, or gene-gene interaction, results from joint effects of genes on a trait; thus, the same alleles of one gene may display different genetic effects in different genetic backgrounds. In this study, we generalized the coding technique of a natural and orthogonal interaction (NOIA) model for association studies along with gene-gene interactions for dichotomous traits and human complex diseases. The NOIA model which has non-correlated estimators for genetic effects is important for estimating influence from multiple loci. We conducted simulations and data analyses to evaluate the performance of the NOIA model. Both simulation and real data analyses revealed that the NOIA statistical model had higher power for detecting main genetic effects and usually had higher power for some interaction effects than the usual model. Although associated genes have been identified for predisposing people to melanoma risk: HERC2 at 15q13.1, MC1R at 16q24.3 and CDKN2A at 9p21.3, no gene-gene interaction study has been fully explored for melanoma. By applying the NOIA statistical model to a genome-wide melanoma dataset, we confirmed the previously identified significantly associated genes and found potential regions at chromosomes 5 and 4 that may interact with the HERC2 and MC1R genes, respectively. Our study not only generalized the orthogonal NOIA model but also provided useful insights for understanding the influence of interactions on melanoma risk. [ABSTRACT FROM AUTHOR]

Individual genome-wide association (GWA) studies and their meta-analyses represent two approaches for identifying genetic loci associated with complex diseases/traits. Inconsistent findings and non-replicability between individual GWA studies and meta-analyses are commonly observed, hence posing the critical question as to how to interpret their respective results properly. In this study, we performed a series of simulation studies to investigate and compare the statistical properties of the two approaches. Our results show that (1) as expected, meta-analysis of larger sample size is more powerful than individual GWA studies under the ideal setting of population homogeneity among individual studies; (2) under the realistic setting of heterogeneity among individual studies, detection of heterogeneity is usually difficult and meta-analysis (even with the random-effects model) may introduce elevated false positive and/or negative rates; (3) despite relatively small sample size, well-designed individual GWA study has the capacity to identify novel loci for complex traits; (4) replicability between meta-analysis and independent individual studies or between independent meta-analyses is limited, and thus inconsistent findings are not unexpected. [ABSTRACT FROM AUTHOR]

Cigarette smoking is an environmental risk factor for many chronic diseases, and disease risk can often be managed by smoking control. Smoking can induce cellular and molecular changes, including epigenetic modification, but the short- and long-term epigenetic modifications caused by cigarette smoking at the gene level have not been well understood. Recent studies have identified smoking-related DNA methylation (DNAm) sites in Caucasians. To determine whether the same DNAm sites associate with smoking in African Americans, and to identify novel smoking-related DNAm sites, we conducted a methylome-wide association study of cigarette smoking using a discovery sample of 972 African Americans, and a replication sample of 239 African Americans with two array-based methods. Among 15 DNAm sites significantly associated with smoking after correction for multiple testing in our discovery sample, 5 DNAm sites are replicated in an independent cohort, and 14 sites in the replication sample have effects in the same direction as in the discovery sample. The top two smoking-related DNAm sites in F2RL3 (factor II receptor-like 3) and GPR15 (G-protein-coupled receptor 15) observed in African Americans are consistent with previous findings in Caucasians. The associations between the replicated DNAm sites and smoking remain significant after adjusting for genetic background. Despite the distinct genetic background between African Americans and Caucasians, the DNAm from the two ethnic groups shares common associations with cigarette smoking, which suggests a common molecular mechanism of epigenetic modification influenced by environmental exposure. [ABSTRACT FROM AUTHOR]

Human height is a complex genetic trait with high heritability but discovery efforts in Asian populations are limited. We carried out a meta-analysis of genome-wide association studies (GWAS) for height in 6,534 subjects with in silico replication of 1,881 subjects in Han Chinese. We identified three novel loci reaching the genome-wide significance threshold ( P < 5 × 10), which mapped in or near ZNF638 (rs12612930, P = 2.02 × 10), MAML2 (rs11021504, P = 7.81 × 10), and C18orf12 (rs11082671, P = 1.87 × 10). We also confirmed two loci previously reported in European populations including CS (rs3816804, P = 2.63 × 10) and CYP19A1 (rs3751599, P = 4.80 × 10). In addition, we provided evidence supporting 35 SNPs identified by previous GWAS ( P < 0.05). Our study provides new insights into the genetic determination of biological regulation of human height. [ABSTRACT FROM AUTHOR]

Diseases such as type 2 diabetes (T2D) result from environmental and genetic factors, and risk varies considerably in the population. T2D-related genetic loci discovered to date explain only a small portion of the T2D heritability. Some heritability may be due to gene-environment interactions. However, documenting these interactions has been difficult due to low availability of concurrent genetic and environmental measures, selection bias, and challenges in controlling for multiple hypothesis testing. Through genome-wide association studies (GWAS), investigators have identified over 90 single nucleotide polymorphisms (SNPs) associated to T2D. Using a method analogous to GWAS [environment-wide association study (EWAS)], we found five environmental factors associated with the disease. By focusing on risk factors that emerge from GWAS and EWAS, it is possible to overcome difficulties in uncovering gene-environment interactions. Using data from the National Health and Nutrition Examination Survey (NHANES), we screened 18 SNPs and 5 serum-based environmental factors for interaction in association to T2D. We controlled for multiple hypotheses using false discovery rate (FDR) and Bonferroni correction and found four interactions with FDR <20 %. The interaction between rs13266634 (SLC30A8) and trans-β-carotene withstood Bonferroni correction (corrected p = 0.006, FDR <1.5 %). The per-risk-allele effect sizes in subjects with low levels of trans-β-carotene were 40 % greater than the marginal effect size [odds ratio (OR) 1.8, 95 % CI 1.3-2.6]. We hypothesize that impaired function driven by rs13266634 increases T2D risk when combined with serum levels of nutrients. Unbiased consideration of environmental and genetic factors may help identify larger and more relevant effect sizes for disease associations. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) of obesity measures have identified associations with single nucleotide polymorphisms (SNPs). However, no large-scale evaluation of gene-environment interactions has been performed. We conducted a search of gene-environment (G × E) interactions in post-menopausal African-American and Hispanic women from the Women's Health Initiative SNP Health Association Resource GWAS study. Single SNP linear regression on body mass index (BMI) and waist-to-hip circumference ratio (WHR) adjusted for multidimensional-scaling-derived axes of ancestry and age was run in race-stratified data with 871,512 SNPs available from African-Americans ( N = 8,203) and 786,776 SNPs from Hispanics ( N = 3,484). Tests of G × E interaction at all SNPs for recreational physical activity (m h/week), dietary energy intake (kcal/day), alcohol intake (categorical), cigarette smoking years, and cigarette smoking (ever vs. never) were run in African-Americans and Hispanics adjusted for ancestry and age at interview, followed by meta-analysis of G × E interaction terms. The strongest evidence for concordant G × E interactions in African-Americans and Hispanics was for smoking and marker rs10133840 (Q statistic P = 0.70, beta = −0.01, P = 3.81 × 10) with BMI as the outcome. The strongest evidence for G × E interaction within a cohort was in African-Americans with WHR as outcome for dietary energy intake and rs9557704 (SNP × kcal = −0.04, P = 2.17 × 10). No results exceeded the Bonferroni-corrected statistical significance threshold. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) in diverse populations are needed to reveal variants that are more common and/or limited to defined populations. We conducted a GWAS of breast cancer in women of African ancestry, with genotyping of >1,000,000 SNPs in 3,153 African American cases and 2,831 controls, and replication testing of the top 66 associations in an additional 3,607 breast cancer cases and 11,330 controls of African ancestry. Two of the 66 SNPs replicated ( p < 0.05) in stage 2, which reached statistical significance levels of 10 and 10 in the stage 1 and 2 combined analysis (rs4322600 at chromosome 14q31: OR = 1.18, p = 4.3 × 10; rs10510333 at chromosome 3p26: OR = 1.15, p = 1.5 × 10). These suggestive risk loci have not been identified in previous GWAS in other populations and will need to be examined in additional samples. Identification of novel risk variants for breast cancer in women of African ancestry will demand testing of a substantially larger set of markers from stage 1 in a larger replication sample. [ABSTRACT FROM AUTHOR]

Many anthropometric measures, including body mass index (BMI), waist-to-hip ratio (WHR), and subcutaneous fat thickness, are used as indicators of nutritional status, fertility and predictors of future health outcomes. While BMI is currently the best available estimate of body adiposity, WHR and skinfold thickness at various sites (biceps, triceps, suprailiac, and subscapular) are used as indices of body fat distribution. Copy number variation (CNV) is an attractive emerging approach to the study of associations with various diseases. In this study, we investigated the dosage effect of genes in the CNV genome widely associated with fat distribution phenotypes in large cohorts. We used the Affymetrix genome-wide human SNP Array 5.0 data of 8,842 healthy unrelated adults in KARE cohorts and identified CNVs associated with BMI and fat distribution-related traits including WHR and subcutaneous skinfold thickness at suprailiac (SUP) and subscapular (SUB) sites. CNV segmentation of each chromosome was performed using Golden Helix SVS 7.0, and single regression analysis was used to identify CNVs associated with each phenotype. We found one CNV for BMI, 287 for WHR, 2,157 for SUP, and 2,102 for SUB at the 5 % significance level after Holm-Bonferroni correction. Genes included in the CNV were used for the analysis of functional annotations using the Database for Annotation, Visualization and Integrated Discovery (DAVID v6.7b) tool. Functional gene classification analysis identified five significant gene clusters (metallothionein, ATP-binding proteins, ribosomal proteins, kinesin family members, and zinc finger proteins) for SUP, three (keratin-associated proteins, zinc finger proteins, keratins) for SUB, and one (protamines) for WHR. BMI was excluded from this analysis because the entire structure of no gene was identified in the CNV. Based on the analysis of genes enriched in the clusters, the fat distribution traits of KARE cohorts were related to the fat redistribution associated with the aging process. In addition to structural variation, dosage effect analysis of genes based on CNV is useful to gain an understanding of the comprehensive biological phenomena underlying particular phenotypes and/or diseases. [ABSTRACT FROM AUTHOR]

The proportion of never smoker non-small cell lung cancer (NSCLC) in Asia is about 30-40%. Despite the striking demographics and high prevalence of never smoker NSCLC, the exact causes still remain undetermined. Although several genome wide association (GWA) studies were conducted to find susceptibility loci for lung cancer in never smokers, no regions were replicated except for 5p15.33, suggesting locus heterogeneity and different environmental toxic effects. To identify genetic loci associated with susceptibility of lung cancer in never smokers, we performed a GWA analysis using the Affymetrix 6.0 SNP array. For discovery GWA set, we recruited 446 never smoking Korean patients with NSCLC and 497 normal subjects. We tested association of SNPs with lung cancer susceptibility using the Cochran-Armitage trend test. For validation, 39 SNPs were selected from the top 50 SNPs and five additional SNPs were selected in the DAB1 gene region which showed significant associations in the GWA analysis. The validation SNPs were genotyped in an independent sample including 434 patients and 1,000 controls. Among the 44 validation SNPs, two SNPs (rs11080466 and rs11663246) near the APCDD1, NAPG and FAM38B genes in the 18p11.22 region were replicated. P value of rs11080466 was 1.08 × 10 in the combined sets (2.68 × 10 in the discovery set and 2.60 × 10 in the validation set) and odds ratio was 0.68 (0.58-0.79). We observed similar association for rs11663246. Our result suggests the 18p11.22 region as a novel lung cancer susceptibility locus in never smokers. [ABSTRACT FROM AUTHOR]

dult height is a classic polygenic trait of high narrow-sense heritability ( h = 0.8). In the late nineteenth to early twentieth century, variation in adult height was used as a model to set the foundation of the fields of statistics and quantitative genetics. More recently, with our increasing knowledge concerning the extent of genetic variation in the human genome, human geneticists have used genome-wide association studies to identify hundreds of loci robustly associated with adult height, providing new insights into human growth and development, and into the architecture of complex human traits. In this review, I highlight the progress made in the last 2 years in understanding how genetic variation controls height variation in humans, including non-Caucasian populations and children. [ABSTRACT FROM AUTHOR]

Different populations suffer from different rates of obesity and type-2 diabetes (T2D). Little is known about the genetic or adaptive component, if any, that underlies these differences. Given the cultural, geographic, and dietary variation that accumulated among humans over the last 60,000 years, we examined whether loci identified by genome-wide association studies for these traits have been subject to recent selection pressures. Using genome-wide SNP data on 938 individuals in 53 populations from the Human Genome Diversity Panel, we compare population differentiation and haplotype patterns at these loci to the rest of the genome. Using an 'expanding window' approach (100-1,600 kb) for the individual loci as well as the loci as ensembles, we find a high degree of differentiation for the ensemble of T2D loci. This differentiation is most pronounced for East Asians and sub-Saharan Africans, suggesting that these groups experienced natural selection at loci associated with T2D. Haplotype analysis suggests an excess of obesity loci with evidence of recent positive selection among South Asians and Europeans, compared to sub-Saharan Africans and Native Americans. We also identify individual loci that may have been subjected to natural selection, such as the T2D locus, HHEX, which displays both elevated differentiation and extended haplotype homozygosity in comparisons of East Asians with other groups. Our findings suggest that there is an evolutionary genetic basis for population differences in these traits, and we have identified potential group-specific genetic risk factors. [ABSTRACT FROM AUTHOR]

Osteoporosis is characterized by low bone mineral density and structural deterioration of bone tissue, leading to an increased risk of fractures. It is the most common metabolic bone disorder worldwide, affecting one in three women and one in eight men over the age of 50. In the past 15 years, a large number of genes have been reported as being associated with osteoporosis. However, only in the past 4 years we have witnessed an accelerated pace in identifying and validating osteoporosis susceptibility loci. This increase in pace is mostly due to large-scale association studies, meta-analyses, and genome-wide association studies of both single nucleotide polymorphisms and copy number variations. A comprehensive review of these developments revealed that, to date, at least 15 genes ( VDR, ESR1, ESR2, LRP5, LRP4, SOST, GRP177, OPG, RANK, RANKL, COLIA1, SPP1, ITGA1, SP7, and SOX6) can be reasonably assigned as confirmed osteoporosis susceptibility genes, whereas, another >30 genes are promising candidate genes. Notably, confirmed and promising genes are clustered in three biological pathways, the estrogen endocrine pathway, the Wnt/β-catenin signaling pathway, and the RANKL/RANK/OPG pathway. New biological pathways will certainly emerge when more osteoporosis genes are identified and validated. These genetic findings may provide new routes toward improved therapeutic and preventive interventions of this complex disease. [ABSTRACT FROM AUTHOR]

The human Deltex (DTX1) gene encodes a cytoplasmic protein that functions as a positive regulator of the Notch signaling pathway. We have determined the genomic organization and map location of the human gene. DTX1 encodes a 2.5-kb cDNA that is composed of nine exons. The DTX1 gene maps to chromosomal region 12q24 in the vicinity of the Noonan syndrome critical region. We have fine-mapped DTX1 to within this critical region and evaluate it as a candidate gene for this disorder. [ABSTRACT FROM AUTHOR]

A letter to the editor in response to an article " Male-specific genetic effect on hypertension and metabolic disorders" published in the year 2014 of the issue by S.G. Heo et al is presented.