Genome-wide association study of copy number variation identified gremlin1 as a candidate gene for lean body mass

Multi-omics research in sarcopenia: Current progress and future prospects

Sarcopenia is a systemic disease with progressive and generalized skeletal muscle dysfunction defined by age-related low muscle mass, high content of muscle slow fibers, and low muscle function. Muscle phenotypes and sarcopenia risk are heritable; however, the genetic architecture and molecular mechanisms underlying sarcopenia remain largely unclear. In recent years, significant progress has been made in determining susceptibility loci using genome-wide association studies. In addition, recent advances in omics techniques, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, offer new opportunities to identify novel targets to help us understand the pathophysiology of sarcopenia. However, each individual technology cannot capture the entire view of the biological complexity of this disorder, while integrative multi-omics analyses may be able to reveal new insights. Here, we review the latest findings of multi-omics studies for sarcopenia and provide an in-depth summary of our current understanding of sarcopenia pathogenesis. Leveraging multi-omics data could give us a holistic understanding of sarcopenia etiology that may lead to new clinical applications. This review offers guidance and recommendations for fundamental research, innovative perspectives, and preventative and therapeutic interventions for sarcopenia.

Unveiling genetic variants for age-related sarcopenia by conducting a genome-wide association study on Korean cohorts

Sarcopenia is an age-related disorder characterised by a progressive decrease in skeletal muscle mass. As the genetic biomarkers for sarcopenia are not yet well characterised, this study aimed to investigate the genetic variations related to sarcopenia in a relatively aged cohort, using genome-wide association study (GWAS) meta-analyses of lean body mass (LBM) in 6961 subjects. Two Korean cohorts were analysed, and subgroup GWAS was conducted for appendicular skeletal muscle mass (ASM) and skeletal muscle index. The effects of significant single nucleotide polymorphisms (SNPs) on gene expression were also investigated using multiple expression quantitative trait loci datasets, differentially expressed gene analysis, and gene ontology analyses. Novel genetic biomarkers were identified for LBM (rs1187118; rs3768582) and ASM (rs6772958). Their related genes, including RPS10, NUDT3, NCF2, SMG7, and ARPC5, were differently expressed in skeletal muscle tissue, while GPD1L was not. Furthermore, the 'mRNA destabilisation' biological process was enriched for sarcopenia. Our study identified RPS10, NUDT3, and GPD1L as significant genetic biomarkers for sarcopenia. These genetic loci were related to lipid and energy metabolism, suggesting that genes involved in metabolic dysregulation may lead to the pathogenesis of age-related sarcopenia.

Three pleiotropic loci associated with bone mineral density and lean body mass

Both bone mineral density (BMD) and lean body mass (LBM) are important physiological measures with strong genetic determination. Besides, BMD and LBM might have common genetic factors. Aiming to identify pleiotropic genomic loci underlying BMD and LBM, we performed bivariate genome-wide association study meta-analyses of femoral neck bone mineral density and LBM at arms and legs, and replicated in the large-scale UK Biobank cohort sample. Combining the results from discovery meta-analysis and replication sample, we identified three genomic loci at the genome-wide significance level (p < 5.0 × 10-8): 2p23.2 (lead SNP rs4477866, discovery p = 3.47 × 10-8, replication p = 1.03 × 10-4), 16q12.2 (rs1421085, discovery p = 2.04 × 10-9, replication p = 6.47 × 10-14) and 18q21.32 (rs11152213, discovery p = 3.47 × 10-8, replication p = 6.69 × 10-6). Our findings not only provide useful insights into lean mass and bone mass development, but also enhance our understanding of the potential genetic correlation between BMD and LBM.

Replication of FTO Gene associated with lean mass in a Meta-Analysis of Genome-Wide Association Studies

Sarcopenia is characterized by low skeletal muscle, a complex trait with high heritability. With the dramatically increasing prevalence of obesity, obesity and sarcopenia occur simultaneously, a condition known as sarcopenic obesity. Fat mass and obesity-associated (FTO) gene is a candidate gene of obesity. To identify associations between lean mass and FTO gene, we performed a genome-wide association study (GWAS) of lean mass index (LMI) in 2207 unrelated Caucasian subjects and replicated major findings in two replication samples including 6,004 unrelated Caucasian and 38,292 unrelated Caucasian. We found 29 single nucleotide polymorphisms (SNPs) in FTO significantly associated with sarcopenia (combined p-values ranging from 5.92 × 10⁻¹² to 1.69 × 10⁻⁹). Potential biological functions of SNPs were analyzed by HaploReg v4.1, RegulomeDB, GTEx, IMPC and STRING. Our results provide suggestive evidence that FTO gene is associated with lean mass.

Association of 3p27.1 Variants with Whole Body Lean Mass Identified by a Genome-wide Association Study

Whole body lean mass (WBLM) is a heritable trait predicting sarcopenia. To identify genomic locus underlying WBLM, we performed a genome-wide association study of fat-adjusted WBLM in the Framingham Heart Study (FHS, N = 6,004), and replicated in the Kansas City Osteoporosis Study (KCOS, N = 2,207). We identified a novel locus 3p27.1 that was associated with WBLM (lead SNP rs3732593 P = 7.19 × 10^-8) in the discovery FHS sample, and the lead SNP was successfully replicated in the KCOS sample (one-sided P = 0.04). Bioinformatics analysis found that this SNP and its adjacent SNPs had the function of regulating enhancer activity in skeletal muscle myoblasts cells, further confirming the regulation of WBLM by this locus. Our finding provides new insight into the genetics of WBLM and enhance our understanding of sarcopenia.

Genome-wide Associations Reveal Human-Mouse Genetic Convergence and Modifiers of Myogenesis, CPNE1 and STC2

Muscle bulk in adult healthy humans is highly variable even after height, age, and sex are accounted for. Low muscle mass, due to fewer and/or smaller constituent muscle fibers, would exacerbate the impact of muscle loss occurring in aging or disease. Genetic variability substantially influences muscle mass differences, but causative genes remain largely unknown. In a genome-wide association study (GWAS) on appendicular lean mass (ALM) in a population of 85,750 middle-aged (aged 38-49 years) individuals from the UK Biobank (UKB), we found 182 loci associated with ALM (p < 5 × 10-8). We replicated associations for 78% of these loci (p < 5 × 10-8) with ALM in a population of 181,862 elderly (aged 60-74 years) individuals from UKB. We also conducted a GWAS on hindlimb skeletal muscle mass of 1,867 mice from an advanced intercross between two inbred strains (LG/J and SM/J); this GWAS identified 23 quantitative trait loci. Thirty-eight positional candidates distributed across five loci overlapped between the two species. In vitro studies of positional candidates confirmed CPNE1 and STC2 as modifiers of myogenesis. Collectively, these findings shed light on the genetics of muscle mass variability in humans and identify targets for the development of interventions for treatment of muscle loss. The overlapping results between humans and the mouse model GWAS point to shared genetic mechanisms across species.

Two functional variants at 6p21.1 were associated with lean mass

Background

Low lean body mass is the most important predictor of sarcopenia with strong genetic background. The aim of this study was to uncover genetic factors underlying lean mass development.

Materials and methods

We performed a genome-wide association study (GWAS) of fat-adjusted leg lean mass in the Framingham Heart Study (FHS, N = 6587), and replicated in the Women’s Health Initiative–African American sub-sample (WHI-AA, N = 847) and the Kansas City Osteoporosis Study (KCOS, N = 2219). We also cross-validated significant variants in the publicly available body mass index (BMI) summary results (N ~ 700,000). We then performed a series of functional investigations on the identified variants.

Results

Four correlated SNPs at 6p21.1 were identified at the genome-wide significance (GWS, α = 5.0 × 10⁻⁸) level in the discovery FHS sample (rs551145, rs524533, rs571770, and rs545970, p = 3.40–9.77 × 10⁻⁹), and were successfully replicated in both the WHI-AA and the KCOS samples (one-sided p = 1.61 × 10⁻³–0.04). They were further cross-validated by the large-scale BMI summary results (p = 7.0–9.8 × 10⁻³). Cis-eQTL analyses associated these SNPs with the NFKBIE gene expression. Electrophoresis mobility shift assay (EMSA) in mouse C2C12 myoblast cells implied that rs524533 and rs571770 were bound to an unknown transcription factor in an allelic specific manner, while rs551145 and rs545970 did not. Dual-luciferase reporter assay revealed that both rs524533 and rs571770 downregulated luciferase expression by repressing promoter activity. Moreover, the regulation pattern was allelic specific, strengthening the evidence towards their differential regulatory effects.

Conclusions

Through a large-scale GWAS followed by a series of functional investigations, we identified 2 correlated functional variants at 6p21.1 associated with leg lean mass. Our findings not only enhanced our understanding of molecular basis of lean mass development but also provided useful candidate genes for further functional studies.

Functional genomics applications and therapeutic implications in sarcopenia

The human genome contains around 20,000-25,000 genes coding for 30,000 proteins. Some proteins and genes represent therapeutic targets for human diseases. RNA and protein expression profiling tools allow the study of the molecular basis of aging and drug discovery validation. Throughout the life, there is an age-related and disease-related muscle decline. Sarcopenia is defined as a loss of muscle mass and a decrease in functional properties such as muscle strength and physical performance. Yet, there is still no consensus on the evaluation methods of sarcopenia prognosis. The main challenge of this complex biological phenomena is its multifactorial etiology. Thus, functional genomics methods attempt to shape the related scientific approaches via an innovative in-depth view on sarcopenia. Gene and drug high throughput screening combined with functional genomics allow the generation and the interpretation of a large amount of data related to sarcopenia and therapeutic progress. This review focuses on the application of selected functional genomics techniques such as RNA interference, RNA silencing, proteomics, transgenic mice, metabolomics, genomics, and epigenomics to better understand sarcopenia mechanisms.

Integrating CNVs into meta-QTL identified GBP4 as positional candidate for adult cattle stature

Copy number variation (CNV) of DNA sequences, functionally significant but yet fully ascertained, is believed to confer considerable increments in unexplained heritability of quantitative traits. Identification of phenotype-associated CNVs (paCNVs) therefore is a pressing need in CNV studies to speed up their exploitation in cattle breeding programs. Here, we provided a new avenue to achieve this goal that is to project the published CNV data onto meta-quantitative trait loci (meta-QTL) map which connects causal genes with phenotypes. Any CNVs overlapping meta-QTL therefore will be potential paCNVs. This study reported potential paCNVs in Bos taurus autosome 3 (BTA3). Notably, overview indexes and CNVs both highlighted a narrower region (BTA3 54,500,000-55,000,000 bp, named BTA3_INQTL_6) within one constructed meta-QTL. Then, we ascertained guanylate-binding protein 4 (GBP4) among the nine positional candidate genes was significantly associated with adult cattle stature, including body weight (BW, P < 0.05) and withers height (WHT, P < 0.05), fitting GBP4 CNV either with three levels or with six levels in the model. Although higher copy number downregulated the mRNA levels of GBP2 (P < 0.05) and GBP4 (P < 0.05) in 1-Mb window (54.0-55.0 Mb) in muscle and adipose, additional analyses will be needed to clarify the causality behind the ascertained association.

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 × 10-8) or suggestively genome wide (p < 2.3 × 10-6). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.

Genomics and metabolomics of muscular mass in a community-based sample of UK females

The contribution of specific molecular-genetic factors to muscle mass variation and sarcopenia remains largely unknown. To identify endogenous molecules and specific genetic factors associated with appendicular lean mass (APLM) in the general population, cross-sectional data from the TwinsUK Adult Twin Registry were used. Non-targeted mass spec-based metabolomic profiling was performed on plasma of 3953 females (mostly dizygotic and monozygotic twins). APLM was measured using dual-energy X-ray absorptiometry (DXA) and genotyping was genome-wide (GWAS). Specific metabolites were used as intermediate phenotypes in the identification of single-nucleotide polymorphisms associated with APLM using GWAS. In all, 162 metabolites were found significantly correlated with APLM, and explained 17.4% of its variation. However, the top three of them (unidentified substance X12063, urate, and mannose) explained 11.1% (P ≤ 9.25 × 10(-26)) so each was subjected to GWAS. Each metabolite showed highly significant (P ≤ 9.28 × 10(-46)) associations with genetic variants in the corresponding genomic regions. Mendelian randomization using these SNPs found no evidence for a direct causal effect of these metabolites on APLM. However, using a new software platform for bivariate analysis we showed that shared genetic factors contribute significantly (P ≤ 4.31 × 10(-43)) to variance in both the metabolites and APLM--independent of the effect of the associated SNPs. There are several metabolites, having a clear pattern of genetic inheritance, which are highly significantly associated with APLM and may provide a cheap and readily accessible biomarker of muscle mass. However, the mechanism by which the genetic factor influences muscle mass remains to be discovered.

Quantitative effect of a CNV on a morphological trait in chickens

Copy Number Variation has been associated with morphological traits, developmental defects or disease susceptibility. The autosomal dominant Pea-comb mutation in chickens is due to the massive amplification of a CNV in intron 1 of SOX5 and provides a unique opportunity to assess the effect of variation in the number of repeats on quantitative traits such as comb size and comb mass in Pea-comb chickens. The quantitative variation of comb size was estimated by 2D morphometry and the number of repeats (RQ) was estimated by qPCR, in a total of 178 chickens from 3 experimental lines, two of them showing segregation for the Pea-comb mutation. This study included only Pea-comb chickens. Analysis of variance showed highly significant effects of line and sex on comb measurements. Adult body weight (BW) and RQ were handled as covariates. BW significantly influenced comb mass but not comb size. RQ values significantly influenced comb size, and the linear regression coefficient was highest for heterozygous carriers: the higher the number of repeats, the smaller the comb size. A similar trend was observed for comb mass. The CNV contributed to 3.4% of the phenotypic variance of comb size in heterozygous carriers of the CNV, an order of magnitude frequently encountered for QTLs. Surprisingly, there was no such relationship between RQ values and comb size in the homozygous line. It may be concluded that heterozygosity for a CNV in a non-coding region may contribute to phenotypic plasticity.

Genome-wide association study of copy number variations (CNVs) with opioid dependence

Single-nucleotide polymorphisms that have been associated with opioid dependence (OD) altogether account for only a small proportion of the known heritability. Most of the genetic risk factors are unknown. Some of the 'missing heritability' might be explained by copy number variations (CNVs) in the human genome. We used Illumina HumanOmni1 arrays to genotype 5152 African-American and European-American OD cases and screened controls and implemented combined CNV calling methods. After quality control measures were applied, a genome-wide association study (GWAS) of CNVs with OD was performed. For common CNVs, two deletions and one duplication were significantly associated with OD genome-wide (eg, P=2 × 10(-8) and OR (95% CI)=0.64 (0.54-0.74) for a chromosome 18q12.3 deletion). Several rare or unique CNVs showed suggestive or marginal significance with large effect sizes. This study is the first GWAS of OD using CNVs. Some identified CNVs harbor genes newly identified here to be of biological importance in addiction, whereas others affect genes previously known to contribute to substance dependence risk. Our findings augment our specific knowledge of the importance of genomic variation in addictive disorders, and provide an addiction CNV pool for further research. These findings require replication.

Recent genetic discoveries in osteoporosis, sarcopenia and obesity

Osteoporosis is a skeletal disorder characterized by low bone mineral density (BMD) and an increased susceptibility to fractures. Evidence from genetic studies indicates that BMD, a complex quantitative trait with a normal distribution, is genetically controlled. Genome-wide association studies (GWAS) as well as studies using candidate gene approaches have identified single-nucleotide polymorphisms (SNPs) that are associated with BMD, osteoporosis and osteoporotic fractures. These SNPs have been mapped close to or within genes including those encoding WNT/β-catenin signaling proteins. Understanding the genetics of osteoporosis will help to identify novel candidates for diagnostic and therapeutic targets. Genetic factors are also important for the development of sarcopenia, which is characterized by a loss of lean body mass, and obesity, which is characterized by high fat mass. Hence, in this review, we discuss the genetic factors, identified by genetic studies, which regulate the body components related to osteoporosis, sarcopenia, and obesity.

Large-scale analysis reveals a functional single-nucleotide polymorphism in the 5'-flanking region of PRDM16 gene associated with lean body mass

Genetic factors are important for the development of sarcopenia, a geriatric disorder characterized by low lean body mass. The aim of this study was to search for novel genes that regulate lean body mass in humans. We performed a large-scale search for 250K single-nucleotide polymorphisms (SNPs) associated with bone mineral density (BMD) using SNP arrays in 1081 Japanese postmenopausal women. We focused on an SNP (rs12409277) located in the 5′-flanking region of the PRDM16 (PRD1-BF-1-RIZ1 homologous domain containing protein 16) gene that showed a significant P value in our screening. We demonstrated that PRDM16 gene polymorphisms were significantly associated with total body BMD in 1081 postmenopausal Japanese women. The rs12409277 SNP affected the transcriptional activity of PRDM16. The subjects with one or two minor allele(s) had a higher lean body mass than the subjects with two major alleles. Genetic analyses uncovered the importance of the PRDM16 gene in the regulation of lean body mass.

Endocrine crosstalk between muscle and bone

The musculoskeletal system is a complex organ comprised of the skeletal bones, skeletal muscles, tendons, ligaments, cartilage, joints, and other connective tissue that physically and mechanically interact to provide animals and humans with the essential ability of locomotion. This mechanical interaction is undoubtedly essential for much of the diverse shape and forms observed in vertebrates and even in invertebrates with rudimentary musculoskeletal systems such as fish. It makes sense from a historical point of view that the mechanical theories of musculoskeletal development have had tremendous influence of our understanding of biology, because these relationships are clear and palpable. Less visible to the naked eye or even to the microscope is the biochemical interaction among the individual players of the musculoskeletal system. It was only in recent years that we have begun to appreciate that beyond this mechanical coupling of muscle and bones, these 2 tissues function at a higher level through crosstalk signaling mechanisms that are important for the function of the concomitant tissue. Our brief review attempts to present some of the key concepts of these new concepts and is outline to present muscles and bones as secretory/endocrine organs, the evidence for mutual genetic and tissue interactions, pathophysiological examples of crosstalk, and the exciting new directions for this promising field of research aimed at understanding the biochemical/molecular coupling of these 2 intimately associated tissues.

A genome-wide association study on copy-number variation identifies a 11q11 loss as a candidate susceptibility variant for colorectal cancer

Colorectal cancer (CRC) is a complex disease, and therefore its development is determined by the combination of both environmental factors and genetic variants. Although genome-wide association studies (GWAS) of SNP variation have conveniently identified 20 genetic variants so far, a significant proportion of the observed heritability is yet to be explained. Common copy-number variants (CNVs) are one of the most important genomic sources of variability, and hence a potential source to explain part of this missing genetic fraction. Therefore, we have performed a GWAS on CNVs to explore the relationship between common structural variation and CRC development. Phase 1 of the GWAS consisted of 881 cases and 667 controls from a Spanish cohort. Copy-number status was validated by quantitative PCR for each of those common CNVs potentially associated with CRC in phase I. Subsequently, SNPs were chosen as proxies for the validated CNVs for phase II replication (1,342 Spanish cases and 1,874 Spanish controls). Four common CNVs were found to be associated with CRC and were further replicated in Phase II. Finally, we found that SNP rs1944682, tagging a 11q11 CNV, was nominally associated with CRC susceptibility (p value = 0.039; OR = 1.122). This locus has been previously related to extreme obesity phenotypes, which could suggest a relationship between body weight and CRC susceptibility.

Genome-wide association study identified copy number variants important for appendicular lean mass

Skeletal muscle is a major component of the human body. Age-related loss of muscle mass and function contributes to some public health problems such as sarcopenia and osteoporosis. Skeletal muscle, mainly composed of appendicular lean mass (ALM), is a heritable trait. Copy number variation (CNV) is a common type of human genome variant which may play an important role in the etiology of many human diseases. In this study, we performed genome-wide association analyses of CNV for ALM in 2,286 Caucasian subjects. We then replicated the major findings in 1,627 Chinese subjects. Two CNVs, CNV1191 and CNV2580, were detected to be associated with ALM (p = 2.26×10⁻² and 3.34×10⁻³, respectively). In the Chinese replication sample, the two CNVs achieved p-values of 3.26×10⁻² and 0.107, respectively. CNV1191 covers a gene, GTPase of the immunity-associated protein family (GIMAP1), which is important for skeletal muscle cell survival/death in humans. CNV2580 is located in the Serine hydrolase-like protein (SERHL) gene, which plays an important role in normal peroxisome function and skeletal muscle growth in response to mechanical stimuli. In summary, our study suggested two novel CNVs and the related genes that may contribute to variation in ALM.

Genetic analysis of low BMI phenotype in the Utah Population Database

The low body mass index (BMI) phenotype of less than 18.5 has been linked to medical and psychological morbidity as well as increased mortality risk. Although genetic factors have been shown to influence BMI across the entire BMI, the contribution of genetic factors to the low BMI phenotype is unclear. We hypothesized genetic factors would contribute to risk of a low BMI phenotype. To test this hypothesis, we conducted a genealogy data analysis using height and weight measurements from driver's license data from the Utah Population Data Base. The Genealogical Index of Familiality (GIF) test and relative risk in relatives were used to examine evidence for excess relatedness among individuals with the low BMI phenotype. The overall GIF test for excess relatedness in the low BMI phenotype showed a significant excess over expected (GIF 4.47 for all cases versus 4.10 for controls, overall empirical p-value<0.001). The significant excess relatedness was still observed when close relationships were ignored, supporting a specific genetic contribution rather than only a family environmental effect. This study supports a specific genetic contribution in the risk for the low BMI phenotype. Better understanding of the genetic contribution to low BMI holds promise for weight regulation and potentially for novel strategies in the treatment of leanness and obesity.

Copy number variation in hereditary non-polyposis colorectal cancer

Hereditary non-polyposis colorectal cancer (HNPCC) is the commonest form of inherited colorectal cancer (CRC) predisposition and by definition describes families which conform to the Amsterdam Criteria or reiterations thereof. In ~50% of patients adhering to the Amsterdam criteria germline variants are identified in one of four DNA Mismatch repair (MMR) genes MLH1, MSH2, MSH6 and PMS2. Loss of function of any one of these genes results in a failure to repair DNA errors occurring during replication which can be most easily observed as DNA microsatellite instability (MSI)—a hallmark feature of this disease. The remaining 50% of patients without a genetic diagnosis of disease may harbour more cryptic changes within or adjacent to MLH1, MSH2, MSH6 or PMS2 or elsewhere in the genome. We used a high density cytogenetic array to screen for deletions or duplications in a series of patients, all of whom adhered to the Amsterdam/Bethesda criteria, to determine if genomic re-arrangements could account for a proportion of patients that had been shown not to harbour causative mutations as assessed by standard diagnostic techniques. The study has revealed some associations between copy number variants (CNVs) and HNPCC mutation negative cases and further highlights difficulties associated with CNV analysis.

Impacts of variation in the human genome on gene regulation

Recent advances in fast and inexpensive DNA sequencing have enabled the extensive study of genomic and transcriptomic variation in humans. Human genomic variation is composed of sequence and structural changes including single-nucleotide and multinucleotide variants, short insertions or deletions (indels), larger copy number variants, and similarly sized copy neutral inversions and translocations. It is now well established that any two genomes differ extensively and that structural changes constitute a prominent source of this variation. There have also been major technological advances in RNA sequencing to globally quantify and describe diversity in transcripts. Large consortia such as the 1000 Genomes Project and the ENCODE (ENCyclopedia Of DNA Elements) Project are producing increasingly comprehensive maps outlining the regions of the human genome containing variants and functional elements, respectively. Integration of genetic variation data and extensive annotation of functional genomic elements, along with the ability to measure global transcription, allow the impacts of genetic variants on gene expression to be resolved. There are several well-established models by which genetic variants affect gene regulation depending on the type, nature, and position of the variant with respect to the affected genes. These effects can be manifested in two ways: changes to transcript sequences and isoforms by coding variants, and changes to transcript abundance by dosage or regulatory variants. Here, we review the current state of how genetic variations impact gene regulation locally and globally in the human genome.

Continuing difficulties in interpreting CNV data: lessons from a genome-wide CNV association study of Australian HNPCC/lynch syndrome patients

Background

Hereditary non-polyposis colorectal cancer (HNPCC)/Lynch syndrome (LS) is a cancer syndrome characterised by early-onset epithelial cancers, especially colorectal cancer (CRC) and endometrial cancer. The aim of the current study was to use SNP-array technology to identify genomic aberrations which could contribute to the increased risk of cancer in HNPCC/LS patients.

Methods

Individuals diagnosed with HNPCC/LS (100) and healthy controls (384) were genotyped using the Illumina Human610-Quad SNP-arrays. Copy number variation (CNV) calling and association analyses were performed using Nexus software, with significant results validated using QuantiSNP. TaqMan Copy-Number assays were used for verification of CNVs showing significant association with HNPCC/LS identified by both software programs.

Results

We detected copy number (CN) gains associated with HNPCC/LS status on chromosome 7q11.21 (28% cases and 0% controls, Nexus; p = 3.60E-20 and QuantiSNP; p < 1.00E-16) and 16p11.2 (46% in cases, while a CN loss was observed in 23% of controls, Nexus; p = 4.93E-21 and QuantiSNP; p = 5.00E-06) via in silico analyses. TaqMan Copy-Number assay was used for validation of CNVs showing significant association with HNPCC/LS. In addition, CNV burden (total CNV length, average CNV length and number of observed CNV events) was significantly greater in cases compared to controls.

Conclusion

A greater CNV burden was identified in HNPCC/LS cases compared to controls supporting the notion of higher genomic instability in these patients. One intergenic locus on chromosome 7q11.21 is possibly associated with HNPCC/LS and deserves further investigation. The results from this study highlight the complexities of fluorescent based CNV analyses. The inefficiency of both CNV detection methods to reproducibly detect observed CNVs demonstrates the need for sequence data to be considered alongside intensity data to avoid false positive results.

Genetics and hypertension: is it time to change my practice?

Recent advances in genotyping technology and in particular a number of large-scale genome-wide association studies have helped to unravel the genetic basis of hypertension. Although our knowledge is still far from being complete it is important to ask how genetic findings could be translated to clinical practice. In a first step we summarize the strategies to dissect the genetics of hypertension from candidate gene studies to genome-wide association studies and recent sequencing experiments. The greatest hope in this context is the development of new drugs that are based on newly discovered pathophysiological principles. We describe examples where significant therapeutic effects are achieved with agents targeting pathways that contribute only small amounts to the genetic variability of a phenotype. There are good reasons to believe that new drugs will be developed based on genetic data in hypertension. We also highlight the potential for pharmacogenetics and risk stratification. The former is not currently supported by a larger body of evidence, but well designed studies are under way. The latter needs to follow the same principles for evaluation of other novel biomarkers of cardiovascular risk and is unlikely to influence clinical practice in the next few years.

Genetic aspects of skeletal muscle strength and mass with relevance to sarcopenia

Skeletal muscle is a highly heritable quantitative trait, with heritability estimates ranging 30-85% for muscle strength and 50-80% for lean mass. That strong genetic contribution indicates the possibility of using genetic information to individualize treatments for sarcopenia or even aid in prevention strategies through the use of genetic screening prior to the functional limitations. Though these possibilities provide the rationale for genetic studies of skeletal muscle traits, few genes have been identified that appear to contribute to variation in either skeletal muscle strength or mass phenotypes, and sarcopenia per se is remarkably understudied as a trait in this regard. This review examines the heritability of skeletal muscle traits, findings of linkage and genome-wide association analyses and impact of specific genes and gene-sequence variants on these traits as relevant to sarcopenia. Despite considerable work in the area, the genetic underpinnings of skeletal muscle traits remain largely unknown and the genetic aspects of sarcopenia are even less clear. Large-scale longitudinal clinical studies relying on advanced genome-wide association and other techniques are needed to provide further insights into the genes and gene variants that contribute to skeletal muscle strength and mass, and ultimately to susceptibility to sarcopenia.