Challenges in reproducibility of genetic association studies: lessons learned from the obesity field

Medical semiology of patients with monogenic obesity: A systematic review

Patients with monogenic obesity display numerous medical features on top of hyperphagic obesity, but no study to date has provided an exhaustive description of their semiology. Two reviewers independently conducted a systematic review of MEDLINE, Embase, and Web of Science Core Collection databases from inception to January 2022 to identify studies that described symptoms of patients carrying pathogenic mutations in at least one of eight monogenic obesity genes (ADCY3, LEP, LEPR, MC3R, MC4R, MRAP2, PCSK1, and POMC). Of 5207 identified references, 269 were deemed eligible after title and abstract screening, full-text reading, and risk of bias and quality assessment. Data extraction included mutation spectrum and mode of inheritance, clinical presentation (e.g., anthropometry, energy intake and eating behaviors, digestive function, puberty and fertility, cognitive features, infectious diseases, morphological characteristics, chronic respiratory disease, and cardiovascular disease), biological characteristics (metabolic profile, endocrinology, hematology), radiological features, and treatments. The review provides an exhaustive description of mandatory, non-mandatory, and unique symptoms in heterozygous and homozygous carriers of mutation in eight monogenic obesity genes. This information is critical to help clinicians to orient genetic testing in subsets of patients with suspected monogenic obesity and provide actionable treatments (e.g., recombinant leptin and MC4R agonist).

Genetic polymorphisms and platinum-induced hematological toxicity: a systematic review

Background

Platinum-based chemotherapy bring severe hematological toxicity that can lead to dose reduction or discontinuation of therapy. Genetic variations have been reported to influence the risk and extent of hematological toxicity; however, the results are controversial and a comprehensive overview is lacking. This systematic review aimed to identify genetic biomarkers of platinum-induced hematological toxicity.

Method

Pubmed, Embase and Web of science database were systematically reviewed for studies that evaluated the association of genetic variants and platinum-related hematological toxicity in tumor patients with no prior history of chemotherapy or radiation, published from inception to the 28th of January 2022. The studies should have specific toxicity scoring system as well as defined toxicity end-point. The quality of reporting was assessed using the Strengthening the Reporting of Genetic Association Studies (STREGA) checklist. Results were summarized using narrative synthesis.

Results

83 studies were eligible with over 682 single-nucleotide polymorphisms across 110 genes. The results are inconsistent and diverse with methodological issues including insufficient sample size, population stratification, various treatment schedule and toxicity end-point, and inappropriate statistics. 11 SNPs from 10 genes (ABCB1 rs1128503, GSTP1 rs1695, GSTM1 gene deletion, ERCC1 rs11615, ERCC1 rs3212986, ERCC2 rs238406, XPC rs2228001, XPCC1 rs25487, MTHFR rs1801133, MDM2 rs2279744, TP53 rs1042522) had consistent results in more than two independent populations. Among them, GSTP1 rs1695, ERCC1 rs11615, ERCC1 rs3212986, and XRCC1 rs25487 present the most promising results.

Conclusion

Even though the results are inconsistent and several methodological concerns exist, this systematic review identified several genetic variations that deserve validation in well-defined studies with larger sample size and robust methodology.

Systematic Review Registration

https://www.crd.york.ac.uk/, identifier CRD42021234164.

Analysis of a genetic region affecting mouse body weight

Genetic factors affect an individual's risk of developing obesity, but in most cases each genetic variant has a small effect. Discovery of genes that regulate obesity may provide clues about its underlying biological processes and point to new ways the disease can be treated. Preclinical animal models facilitate genetic discovery in obesity because environmental factors can be better controlled compared with the human population. We studied inbred mouse strains to identify novel genes affecting obesity and glucose metabolism. BTBR T+ Itpr3^tf/J (BTBR) mice are fatter and more glucose intolerant than C57BL/6J (B6) mice. Prior genetic studies of these strains identified an obesity locus on chromosome 2. Using congenic mice, we found that obesity was affected by a ∼316 kb region, with only two known genes, pyruvate dehydrogenase kinase 1 (Pdk1) and integrin α 6 (Itga6). Both genes had mutations affecting their amino acid sequence and reducing mRNA levels. Both genes have known functions that could modulate obesity, lipid metabolism, insulin secretion, and/or glucose homeostasis. We hypothesized that genetic variation in or near Pdk1 or Itga6 causing reduced Pdk1 and Itga6 expression would promote obesity and impaired glucose tolerance. We used knockout mice lacking Pdk1 or Itga6 fed an obesigenic diet to test this hypothesis. Under the conditions we studied, we were unable to detect an individual contribution of either Pdk1 or Itga6 to body weight. During our studies, with conditions outside our control, we were unable to reproduce some of our previous body weight data. However, we identified a previously unknown role for Pdk1 in cardiac cholesterol metabolism providing the basis for future investigations. The studies described in this paper highlight the importance and the challenge using physiological outcomes to study obesity genes in mice.

Low-frequency Coding Variants Associated With Body Mass Index Affect the Success of Bariatric Surgery

CONTEXT

A recent study identified 14 low-frequency coding variants associated with body mass index (BMI) in 718 734 individuals predominantly of European ancestry.

OBJECTIVE

We investigated the association of 2 genetic scores (GS) with i) the risk of severe/morbid obesity, ii) BMI variation before weight-loss intervention, iii) BMI change in response to an 18-month lifestyle/behavioral intervention program, and iv) BMI change up to 24 months after bariatric surgery.

METHODS

The 14 low-frequency coding variants were genotyped or sequenced in 342 French adults with severe/morbid obesity and 574 French adult controls from the general population. We built risk and protective GS based on 6 BMI-increasing and 5 BMI-decreasing low-frequency coding variants that were polymorphic in our study.

RESULTS

While the risk GS was not associated with severe/morbid obesity status, BMI-decreasing low-frequency coding variants were significantly less frequent in patients with severe/morbid obesity than in French adults from the general population. Neither the risk nor the protective GS was associated with BMI before intervention in patients with severe/morbid obesity, nor did they affect BMI change in response to a lifestyle/behavioral modification program. The protective GS was associated with a greater BMI decrease following bariatric surgery. The risk and protective GS were associated with a higher and lower risk of BMI regain after bariatric surgery.

CONCLUSION

Our data indicate that in populations of European descent, low-frequency coding variants associated with BMI in the general population also affect the outcomes of bariatric surgery in patients with severe/morbid obesity.

The MC4R p.Ile269Asn mutation confers a high risk for type 2 diabetes in the Mexican population via obesity dependent and independent effects

We investigated the association between the loss-of-function mutation MC4R p.Ile269Asn and T2D risk in the Mexican population. We enrolled 6929 adults [3175 T2D cases and 3754 normal glucose tolerant (NGT) controls] and 994 NGT children in the study. Anthropometric data and T2D-related quantitative traits were studied in 994 NGT children and 3754 NGT adults. The MC4R p.Ile269Asn mutation was genotyped using TaqMan. The MC4R p.Ile269Asn mutation was associated with T2D [OR = 2.00, 95% confidence interval (CI) 1.35-2.97, p = 0.00057] in Mexican adults. Additional adjustment for body-mass index (BMI) attenuated but did not remove the association (OR = 1.70, 95% CI 1.13-2.56, p = 0.011). The MC4R p.Ile269Asn mutation was associated with T2D (OR = 1.88, 95% CI 1.14-3.08, p = 0.013) in a subset of 1269 T2D cases and 1269 NGT controls matched for sex, age, and BMI. A mediation analysis estimated that BMI accounts for 22.7% of the association between MC4R p.Ile269Asn mutation and T2D risk (p = 4.55 × 10^-6). An association was observed between the MC4R p.Ile269Asn mutation and BMI in NGT children and adults (children: beta = 3.731 ± 0.958, p = 0.0001; adults: beta = 2.269 ± 0.536, p = 2.3 × 10^-5). In contrast, the mutation was not associated with T2D-related quantitative traits. We demonstrate that the MC4R p.Ile269Asn mutation predisposes to T2D via obesity-dependent and independent effects in the Mexican population.

Association of the NEGR1 rs2815752 with obesity and related traits in Pakistani females

Introduction: The variant NEGR1 rs2815752 has recently been linked with obesity in Caucasians. However, a very limited number of studies have examined the association of the NEGR1 rs2815752 with overweight/obesity in non-Caucasians with no such study ever performed in Pakistani population. Therefore, the present study was undertaken to seek the association of the rs2815752 with overweight, obesity, and related traits in Pakistanis.Subjects and methods: The study involved 112 overweight/control pairs (total 224) and 194 obese/control pairs (total 388). Anthropometric parameters were measured by employing standard procedures. Metabolic parameters were determined by biochemical assays. Behavioral information was collected through a questionnaire. The rs2815752 was genotyped via TaqMan allelic discrimination assay. Regression analyses were employed to analyze the data in SPSS software.Results: The study revealed significant gender-specific association of the rs2815752 with obesity (OR 3.03; CI 1.19-7.72, p = 0.020) and some obesity-related anomalous anthropometric traits (weight, BMI, waist circumference, hip circumference, and abdominal and supra-iliac skinfold thicknesses) in females according to dominant model (h = 0.023). However, no association of the rs2815752 with obesity-related behavioral and metabolic parameters was observed.Conclusion: The NEGR1 rs2815752 may be associated with obese phenotype and some of the related anthropometric traits in Pakistani females.

Causal Association of Haptoglobin With Obesity in Mexican Children: A Mendelian Randomization Study

CONTEXT

Little is known about the association between haptoglobin level and cardiometabolic traits. A previous genome-wide association study identified rs2000999 in the HP gene as the stronger genetic contributor to serum haptoglobin level in European populations.

OBJECTIVE AND DESIGN

We investigated the association of HP rs2000999 with serum haptoglobin and childhood and adult obesity in up to 540/697 and 592/691 Mexican cases and controls, respectively. Anthropometric and biochemical data were collected. Serum haptoglobin was measured by an immunoturbidimetry assay. HP rs2000999 was genotyped using the TaqMan technology. Mendelian randomization analysis was performed using the Wald and inverse variance weighting methods.

RESULTS

Haptoglobin level was positively associated with childhood and adult obesity. HP rs2000999 G allele was positively associated with haptoglobin level in children and adults. HP rs2000999 G allele was positively associated with childhood but not adult obesity. The association between HP rs2000999 and childhood obesity was removed after adjusting for haptoglobin level. In a Mendelian randomization analysis, haptoglobin level genetically predicted by HP rs2000999 showed a significant causal effect on childhood obesity by the Wald and inverse variance weighting methods.

CONCLUSION

Our data provide evidence for the first time for a causal positive association between serum haptoglobin level and childhood obesity in the Mexican population. Our study contributes to the genetic elucidation of childhood obesity and proposes haptoglobin as an important biomarker and treatment target for obesity.

Applicability of Obesity-Related SNPs and their Effect Size Measures Defined on Populations with European Ancestry for Genetic Risk Estimation among Roma

Investigations on the impact of genetic factors on the development of obesity have been limited regarding the Roma population—the largest and most vulnerable ethnic minority in Europe of Asian origin. Genetic variants identified from genetic association studies are primarily from European populations. With that in mind, we investigated the applicability of data on selected obesity-related single nucleotide polymorphisms (SNPs), obtained from the Hungarian general (HG) population of European origin, on the Hungarian Roma (HR) population. Twenty preselected SNPs in susceptible alleles, known to be significantly associated with obesity-related phenotypes, were used to estimate the effect of these SNPs on body mass index (BMI) and waist circumference (WC) in HG (N = 1783) and HR (N = 1225) populations. Single SNP associations were tested using linear and logistic regression models, adjusted for known covariates. Out of 20 SNPs, four located in FTO (rs1121980, rs1558902, rs9939609, and rs9941349) showed strong association with BMI and WC as continuous variables in both samples. Computations based on Adult Treatment Panel III (ATPIII) and the International Diabetes Federation’s (IDF) European and Asian criteria showed rs9941349 in FTO to be associated only with WC among both populations, and two SNPs (rs2867125, rs6548238) in TMEM18 associated with WC only in HG population. A substantial difference (both in direction and effect size) was observed only in the case of rs1801282 in PPARγ on WC as a continuous outcome. Findings suggest that genetic risk scores based on counting SNPs with relatively high effect sizes, defined based on populations with European ancestry, can sufficiently allow estimation of genetic susceptibility for Roma. Further studies are needed to clarify the role of SNP(s) with protective effect(s).

Benefits and limitations of genome-wide association studies

Genome-wide association studies (GWAS) involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have revolutionized the field of complex disease genetics over the past decade, providing numerous compelling associations for human complex traits and diseases. Despite clear successes in identifying novel disease susceptibility genes and biological pathways and in translating these findings into clinical care, GWAS have not been without controversy. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. In this Review, we comprehensively assess the benefits and limitations of GWAS in human populations and discuss the relevance of performing more GWAS.

Contribution of rare coding mutations in CD36 to type 2 diabetes and cardio-metabolic complications

We sequenced coding regions of the cluster of differentiation 36 (CD36) gene in 184 French individuals of European ancestry presenting simultaneously with type 2 diabetes (T2D), arterial hypertension, dyslipidemia, and coronary heart disease. We identified rare missense mutations (p.Pro191Leu/rs143150225 and p.Ala252Val/rs147624636) in two heterozygous cases. The two CD36 mutation carriers had no family history of T2D and no clustering of cardio-metabolic complications. While the p.Pro191Leu mutation was found in 84 heterozygous carriers from five ethnic groups from the genome aggregation database (global frequency: 0.0297%, N = 141,321), only one European carrier of the p.Ala252Val mutation was identified (global frequency: 0.00040%, N = 125,523). The Pro191 and Ala252 amino acids were not conserved (74.8% and 68.9% across 131 animal species, respectively). In vitro experiments showed that the two CD36 mutant proteins are expressed and trafficked to the plasma membrane where they bind modified low-density-lipoprotein (LDL) cholesterol as normal. However, molecular modelling of the recent CD36 crystal structure showed that Pro191 was located at the exit/entrance gate of the lipid binding chamber and Ala252 was in line with the chamber. Overall, our data do not support a major contribution of CD36 rare coding mutations to T2D and its cardio-metabolic complications in the French population.

Loss-of-function mutations in the melanocortin-3 receptor gene confer risk for human obesity: A systematic review and meta-analysis

The association between rare coding loss-of-function (LOF) mutations in the melanocortin receptor 3 (MC3R) gene and human obesity is controversial. To fill this gap of knowledge, we performed a systematic review and meta-analysis of genetic association studies in all ages and ethnicities. Two reviewers independently performed risk of bias assessment and extracted data. We searched Medline, Embase, Web of Science Core Collection, BIOSIS Preview, CINAHL, ProQuest Dissertations & Theses, and reference lists of relevant studies. All case-control, cross-sectional, prospective, and retrospective studies that evaluated prevalence of rare (less than 1% frequency) coding partial/complete LOF mutations in MC3R among individuals with obesity and normal weight were included. Our systematic search identified 1925 references relevant to the present review. Six studies were deemed eligible. Meta-analysis of 2969 individuals with obesity and 2572 with normal weight showed a positive association between rare heterozygous coding partial/complete LOF mutations in MC3R and obesity in children and adults of European, North African, and Asian ancestries (odds ratio = 3.07; 95% CI, 1.48-7.00; P = 4.2 × 10^-3 ). Our data demonstrates that rare partial/complete LOF mutations in the coding region of MC3R confer three-time increased risk of obesity in humans, and implies that rare genetic variants with intermediate effects contribute to the missing heritability of obesity.

Evaluating the Potential of Younger Cases and Older Controls Cohorts to Improve Discovery Power in Genome-Wide Association Studies of Late-Onset Diseases

For more than a decade, genome-wide association studies have been making steady progress in discovering the causal gene variants that contribute to late-onset human diseases. Polygenic late-onset diseases in an aging population display a risk allele frequency decrease at older ages, caused by individuals with higher polygenic risk scores becoming ill proportionately earlier and bringing about a change in the distribution of risk alleles between new cases and the as-yet-unaffected population. This phenomenon is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes, while for late-onset diseases with relatively lower prevalence and heritability, exemplified by cancers, the effect is significantly lower. In this research, computer simulations have demonstrated that genome-wide association studies of late-onset polygenic diseases showing high cumulative incidence together with high initial heritability will benefit from using the youngest possible age-matched cohorts. Moreover, rather than using age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

Age-related late-onset disease heritability patterns and implications for genome-wide association studies

Genome-wide association studies (GWASs) and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called "missing heritability" problem. Computer simulations of polygenic late-onset diseases (LODs) in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores (PRSs) becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer's disease, coronary artery disease, cerebral stroke, and type 2 diabetes. The incidence rate for LODs grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for GWASs overrepresent older individuals with lower PRSs, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and GWASs. It also explains the relatively constant-with-age heritability found for LODs of lower prevalence, exemplified by cancers.

Population Levels Assessment of the Distribution of Disease-Associated Variants With Emphasis on Armenians - A Machine Learning Approach

Background: During the last decades a number of genome-wide association studies (GWASs) has identified numerous single nucleotide polymorphisms (SNPs) associated with different complex diseases. However, associations reported in one population are often conflicting and did not replicate when studied in other populations. One of the reasons could be that most GWAS employ a case-control design in one or a limited number of populations, but little attention was paid to the global distribution of disease-associated alleles across different populations. Moreover, the majority of GWAS have been performed on selected European, African, and Chinese populations and the considerable number of populations remains understudied. Aim: We have investigated the global distribution of so far discovered disease-associated SNPs across worldwide populations of different ancestry and geographical regions with a special focus on the understudied population of Armenians. Data and Methods: We have used genotyping data from the Human Genome Diversity Project and of Armenian population and combined them with disease-associated SNP data taken from public repositories leading to a final dataset of 44,234 markers. Their frequency distribution across 1039 individuals from 53 populations was analyzed using self-organizing maps (SOM) machine learning. Our SOM portrayal approach reduces data dimensionality, clusters SNPs with similar frequency profiles and provides two-dimensional data images which enable visual evaluation of disease-associated SNPs landscapes among human populations. Results: We find that populations from Africa, Oceania, and America show specific patterns of minor allele frequencies of disease-associated SNPs, while populations from Europe, Middle East, Central South Asia, and Armenia mostly share similar patterns. Importantly, different sets of SNPs associated with common polygenic diseases, such as cancer, diabetes, neurodegeneration in populations from different geographic regions. Armenians are characterized by a set of SNPs that are distinct from other populations from the neighboring geographical regions. Conclusion: Genetic associations of diseases considerably vary across populations which necessitates health-related genotyping efforts especially for so far understudied populations. SOM portrayal represents novel promising methods in population genetic research with special strength in visualization-based comparison of SNP data.

A Candidate-Gene Approach Identifies Novel Associations Between Common Variants in/Near Syndromic Obesity Genes and BMI in Pediatric and Adult European Populations

We hypothesized that monogenic syndromic obesity genes are also involved in the polygenic variation of BMI. Single-marker, tag single nucleotide polymorphism (tagSNP) and gene-based analysis were performed on common variants near 54 syndromic obesity genes. We used publicly available data from meta-analyses of European BMI genome-wide association studies conducted by the Genetic Investigation of ANthropometric Traits (GIANT) Consortium and the UK Biobank (UKB) (N = 681,275 adults). A total of 33 loci were identified, of which 19 of 33 (57.6%) were located at SNPs previously identified by the GIANT Consortium and UKB meta-analysis, 11 of 33 (33.3%) were located at novel SNPs, and 3 of 33 (9.1%) were novel genes identified with gene-based analysis. Both single-marker and tagSNP analyses mapped the previously identified 19 SNPs by the GIANT Consortium and UKB meta-analysis. Gene-based analysis confirmed 15 of 19 (78.9%) of the novel SNPs' associated genes. Of the 11 novel loci, 8 were identified with single-marker analysis and the remaining 3 were identified with tagSNP analysis. Gene-based analysis confirmed 4 of 11 (36.3%) of these loci. Meta-analysis with the Early Growth Genetics (EGG) Consortium (N = 35,668 children) was conducted post hoc for top SNPs, confirming 17 of 33 (51.5%) loci, of which 5 were novel. This study supports evidence for a continuum between rare monogenic syndromic and common polygenic forms of obesity.

Comprehensive identification of pleiotropic loci for body fat distribution using the NHGRI-EBI Catalog of published genome-wide association studies

We conducted a hypothesis-free cross-trait analysis for waist-to-hip ratio adjusted for body mass index (WHR_adjBMI ) loci derived through genome-wide association studies (GWAS). Summary statistics from published GWAS were used to capture all WHR_adjBMI single-nucleotide polymorphisms (SNPs), and their proxy SNPs were identified. These SNPs were used to extract cross-trait associations between WHR_adjBMI SNPs and other traits through the NHGRI-EBI GWAS Catalog. Pathway analysis was conducted for pleiotropic WHR_adjBMI SNPs. We found 160 WHR_adjBMI SNPs and 3675 proxy SNPs. Cross-trait analysis identified 239 associations, of which 100 were for obesity traits. The remaining 139 associations were filtered down to 101 unique linkage disequilibrium block associations, which were grouped into 13 categories: lipids, red blood cell traits, white blood cell counts, inflammatory markers and autoimmune diseases, type 2 diabetes-related traits, adiponectin, cancers, blood pressure, height, neuropsychiatric disorders, electrocardiography changes, urea measurement, and others. The highest number of cross-trait associations were found for triglycerides (n = 10), high-density lipoprotein cholesterol (n = 9), and reticulocyte counts (n = 8). Pathway analysis for WHR_adjBMI pleiotropic SNPs found immune function pathways as the top canonical pathways. Results from our original methodology indicate a novel genetic association between WHR_adjBMI and reticulocyte counts and highlight the pleiotropy between abdominal obesity, immune pathways, and other traits.

Established and emerging strategies to crack the genetic code of obesity

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.

Gain-of-function variants in the melanocortin 4 receptor gene confer susceptibility to binge eating disorder in subjects with obesity: a systematic review and meta-analysis

The association between coding variants in the melanocortin 4 receptor gene (MC4R) and binge eating disorder (BED) in patients with obesity is controversial. Two independent reviewers systematically searched MEDLINE, Embase, PsycINFO, BIOSIS Previews, Web of Science Core Collection and Google Scholar up to February 2018, using terms describing the MC4R gene and BED. Six of 103 identified references were included. Studies examined associations between at least one coding variant/mutation in MC4R and BED and screened for BED as per the Diagnostic and Statistical Manual of Mental Disorders. Risk of bias was assessed using a modified version of the Q-Genie tool, and overall quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation guidance. Meta-analysis was conducted via logistic regression models. A positive association between gain-of-function (GOF) variants in the MC4R and BED was observed (odds ratio [OR] = 3.05; 95% confidence interval [CI]: 1.82, 5.04; p = 1.7 × 10^-5 ), while no association was detected between loss-of-function (LOF) mutations and BED (OR = 1.50; 95% CI: 0.73, 2.96; p = 0.25). Similar results were found after accounting for study quality (GOF variants: OR = 3.15; 95% CI: 1.76, 5.66; p = 1.1 × 10^-4 ; LOF mutations: OR = 1.50; 95% CI: 0.73, 2.97; p = 0.25). Our systematic review and meta-analysis provides evidence that GOF variants as opposed to LOF mutations in MC4R are associated with BED in subjects with obesity.

Revisiting the evolutionary origins of obesity: lazy versus peppy-thrifty genotype hypothesis

The recent global obesity epidemic is attributed to major societal and environmental changes, such as excessive energy intake and sedentary lifestyle. However, exposure to 'obesogenic' environments does not necessarily result in obesity at the individual level, as 40-75% of body mass index variation in population is attributed to genetic differences. The thrifty genotype theory posits that genetic variants promoting efficient food sequestering and optimal deposition of fat during periods of food abundance were evolutionarily advantageous for the early hunter-gatherer and were positively selected. However, the thrifty genotype is likely too simplistic and fails to provide a justification for the complex distribution of obesity predisposing gene variants and for the broad range of body mass index observed in diverse ethnic groups. This review proposes that gene pleiotropy may better account for the variability in the distribution of obesity susceptibility alleles across modern populations. We outline the lazy-thrifty versus peppy-thrifty genotype hypothesis and detail the body of evidence in the literature in support of this novel concept. Future population genetics and mathematical modelling studies that account for pleiotropy may further improve our understanding of the evolutionary origins of the current obesity epidemic.

Space Radiation Alters Genotype-Phenotype Correlations in Fear Learning and Memory Tests

Behavioral and cognitive traits have a genetic component even though contributions from individual genes and genomic loci are in many cases modest. Changes in the environment can alter genotype–phenotype relationships. Space travel, which includes exposure to ionizing radiation, constitutes environmental challenges and is expected to induce not only dramatic behavioral and cognitive changes but also has the potential to induce physical DNA damage. In this study, we utilized a genetically heterogeneous mouse model, dense genotype data, and shifting environmental challenges, including ionizing radiation exposure, to explore and quantify the size and stability of the genetic component of fear learning and memory-related measures. Exposure to ionizing radiation and other external stressors altered the genotype–phenotype correlations, although different behavioral and cognitive measures were affected to different extents. Utilizing an integrative genomic approach, we identified pathways and functional ontology categories associated with these behavioral and cognitive measures.

Fine-mapping of 98 obesity loci in Mexican children

BACKGROUND/OBJECTIVES

Mexico has one of the highest prevalence of childhood obesity in the world. Genome-wide association studies (GWAS) for obesity have identified multiple single-nucleotide polymorphisms (SNPs) in populations of European, East Asian, and African descent. The contribution of these loci to obesity in Mexican children is unclear. We assessed the transferability of 98 obesity loci in Mexican children and fine-mapped the association signals.

SUBJECTS/METHODS

The study included 405 and 390 Mexican children with normal weight and obesity. Participants were genotyped with a genome-wide dense SNP array designed for Latino populations, allowing for the analysis of GWAS index SNPs as well as fine-mapping SNPs, totaling 750 SNPs covering 98 loci. Two genetic risk scores (GRS) were constructed: a "discovery GRS" and a "best-associated GRS", representing the number of effect alleles at the GWAS index SNPs and at the best-associated SNPs after fine-mapping for each subject.

RESULTS

Seventeen obesity loci were significantly associated with obesity, and five had fine-mapping SNPs significantly better associated with obesity than their corresponding GWAS index SNPs in Mexican children. Six obesity-associated SNPs significantly departed from additive to dominant (N = 5) or recessive (N = 1) models, and a significant interaction was found between rs274609 (TNNI3K) and rs1010553 (ITIH4) on childhood obesity risk. The best-associated GRS was significantly more associated with childhood obesity (OR = 1.21 per additional risk allele [95%CI:1.17-1.25], P = 4.8 × 10^-25) than the discovery GRS (OR = 1.05 per additional risk allele [95%CI:1.02-1.08], P = 8.0 × 10^-4), and was also associated with waist-to-hip ratio, fasting glucose, fasting insulin and triglyceride levels, the association being mediated by obesity. An overall depletion of obesity risk alleles was observed in Mexican children with normal weight when compared to GWAS discovery populations.

CONCLUSIONS

Our study indicates a partial transferability of GWAS obesity loci in Mexican children, and supports the pertinence of post-GWAS fine-mapping experiments in the admixed Mexican population.

Ethnic and population differences in the genetic predisposition to human obesity

Obesity rates have escalated to the point of a global pandemic with varying prevalence across ethnic groups. These differences are partially explained by lifestyle factors in addition to genetic predisposition to obesity. This review provides a comprehensive examination of the ethnic differences in the genetic architecture of obesity. Using examples from evolution, heritability, admixture, monogenic and polygenic studies of obesity, we provide explanations for ethnic differences in the prevalence of obesity. The debate over definitions of race and ethnicity, the advantages and limitations of multi-ethnic studies and future directions of research are also discussed. Multi-ethnic studies have great potential to provide a better understanding of ethnic differences in the prevalence of obesity that may result in more targeted and personalized obesity treatments.

MetaGenyo: a web tool for meta-analysis of genetic association studies

Background

Genetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise.

Results

We have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results.

Conclusions

MetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/.

Electronic supplementary material

The online version of this article (10.1186/s12859-017-1990-4) contains supplementary material, which is available to authorized users.

Rationale and design of GENEiUS: a prospective observational study on the genetic and environmental determinants of body mass index evolution in Canadian undergraduate students

INTRODUCTION

Obesity is a global epidemic and is a risk factor for developing other comorbidities. Young adulthood is a critical period for body weight change and establishing healthy lifestyle behaviours. The 'Freshman 15' suggests that undergraduate students gain 15 lbs (6.8 kg) during their first year of university, although evidence estimates a more modest weight gain of approximately 3-5 lbs (1.4-2.3 kg). Previous studies have only investigated weight change in the first year and do not study potential risk factors. Genetic and EnviroNmental Effects on weight in University Students (GENEiUS) is a prospective observational study which will investigate the environmental and biological determinants of weight change in undergraduate students over 4 years.

METHODS AND ANALYSIS

The GENEiUS study will recruit 2500 multiethnic undergraduates aged 17-25 years at McMaster University at the start of their first year and will follow them every 6 months for 4 years. Primary outcomes are obesity traits: body mass index, waist circumference, waist-to-hip ratio, body fat mass and body fat percentage. The contribution of well-established and novel genetic variants for obesity traits and heritability values will be derived from whole-genome single-nucleotide polymorphism genotyping arrays. Civil status, age, sex, ethnicity, length of residence in Canada, religiosity, energy intake, physical activity, exercise motivation, electronic screen time, sleep patterns, history of assault, smoking status, alcohol consumption, medication and drug use, stress, impulsivity, body image perception, self-esteem, anxiety, eating disorders and depression will be investigated for their effect on obesity traits. The findings of the GENEiUS study will be used to help design obesity prevention programme in North American universities with multiethnic populations.

ETHICS AND DISSEMINATION

Ethical approval of the study protocol has been obtained from the Hamilton Integrated Research Ethics Board. Study results will be disseminated through scientific publications, scholarly meetings, and collaborative meetings with university administration and student groups.

Parental and offspring contribution of genetic markers of adult blood pressure in early life: The FAMILY study

Previous genome wide association studies (GWAS) identified associations of multiple common variants with diastolic and systolic blood pressure traits in adults. However, the contribution of these loci to variations of blood pressure in early life is unclear. We assessed the child and parental contributions of 33 GWAS single-nucleotide polymorphisms (SNPs) for blood pressure in 1,525 participants (515 children, 406 mothers and 237 fathers) of the Family Atherosclerosis Monitoring In early life (FAMILY) study followed-up for 5 years. Two genotype scores for systolic (29 SNPs) and diastolic (24 SNPs) blood pressure were built. Linear mixed-effect regressions showed significant association between rs1378942 in CSK and systolic blood pressure (β = 0.98±0.46, P = 3.4×10⁻²). The child genotype scores for diastolic and systolic blood pressure were not associated in children. Nominally significant parental genetic effects were found between the SNPs rs11191548 (CYP17A1) (paternal, β = 2.78±1.49, P = 6.1×10⁻² for SBP and β = 3.60±1.24, P = 3.7×10⁻³ for DBP), rs17367504 (MTHFR) (paternal, β = 2.42±0.93, P = 9.3×10⁻³ for SBP and β = 1.89±0.80, P = 1.8×10⁻² for DBP and maternal, β = -1.32±0.60, P = 2.9×10⁻² and β = -1.97±0.77, P = 1.0×10⁻², for SBP and DBP respectively) and child blood pressure. Our study supports the view that adult GWAS loci have a limited impact on blood pressure during the five first years of life. The parental genetic effects observed on blood pressure in children may suggest epigenetic mechanisms in the transmission of the risk of hypertension. Further replication is needed to confirm our results.

The association of insertions/deletions (INDELs) and variable number tandem repeats (VNTRs) with obesity and its related traits and complications

BACKGROUND

Despite the fact that insertions/deletions (INDELs) are the second most common type of genetic variations and variable number tandem repeats (VNTRs) represent a large portion of the human genome, they have received far less attention than single nucleotide polymorphisms (SNPs) and larger forms of structural variation like copy number variations (CNVs), especially in genome-wide association studies (GWAS) of complex diseases like polygenic obesity. This is exemplified by the vast amount of review papers on the role of SNPs and CNVs in obesity, its related traits (like anthropometric measurements, biochemical variables, and eating behavior), and its related complications (like hypertension, hypertriglyceridemia, hypercholesterolemia, and insulin resistance-collectively known as metabolic syndrome). Hence, this paper reviews the types of INDELs and VNTRs that have been studied for association with obesity and its related traits and complications. These INDELs and VNTRs could be found in the obesity loci or genes from the earliest GWAS and candidate gene association studies, like FTO, genes in the leptin-proopiomelanocortin pathway, and UCP2/3. Given the important role of the brain serotonergic and dopaminergic reward system in obesity susceptibility, the association of INDELs and VNTRs in these neurotransmitters' metabolism and transport genes with obesity is also reviewed. Next, the role of INS VNTR in obesity and its related traits is questionable, since recent large-scale studies failed to replicate the earlier positive associations. As obesity results in chronic low-grade inflammation of the adipose tissue, the proinflammatory cytokine gene IL1RA and anti-inflammatory cytokine gene IL4 have VNTRs that are implicated in obesity. A systemic proinflammatory state in combination with activation of the renin-angiotensin system and decreased nitric oxide bioavailability as found in obesity leads to endothelial dysfunction. This explains why VNTR and INDEL in eNOS and ACE, respectively, could be predisposing factors of obesity. Finally, two novel genes, DOCK5 and PER3, which are involved in the regulation of the Akt/MAPK pathway and circadian rhythm, respectively, have VNTRs and INDEL that might be associated with obesity.

SHORT CONCLUSION

In conclusion, INDELs and VNTRs could have important functional consequences in the pathophysiology of obesity, and research on them should be continued to facilitate obesity prediction, prevention, and treatment.

A systematic review of genetic syndromes with obesity

Syndromic monogenic obesity typically follows Mendelian patterns of inheritance and involves the co-presentation of other characteristics, such as mental retardation, dysmorphic features and organ-specific abnormalities. Previous reviews on obesity have reported 20 to 30 syndromes but no systematic review has yet been conducted on syndromic obesity. We searched seven databases using terms such as 'obesity', 'syndrome' and 'gene' to conduct a systematic review of literature on syndromic obesity. Our literature search identified 13,719 references. After abstract and full-text review, 119 relevant papers were eligible, and 42 papers were identified through additional searches. Our analysis of these 161 papers found that 79 obesity syndromes have been reported in literature. Of the 79 syndromes, 19 have been fully genetically elucidated, 11 have been partially elucidated, 27 have been mapped to a chromosomal region and for the remaining 22, neither the gene(s) nor the chromosomal location(s) have yet been identified. Interestingly, 54.4% of the syndromes have not been assigned a name, whereas 13.9% have more than one name. We report on organizational inconsistencies (e.g. naming discrepancies and syndrome classification) and provide suggestions for improvements. Overall, this review illustrates the need for increased clinical and genetic research on syndromes with obesity.

Genetic and familial predisposition to rotator cuff disease: a systematic review

BACKGROUND

Rotator cuff disease is a common disorder leading to shoulder pain and loss of function. Its etiology in atraumatic cases is uncertain and is likely to extend beyond repetitive microtrauma or overuse. Our objective was to determine whether there is a genetic or familial predisposition to rotator cuff disease.

METHODS

A literature search of PubMed and Embase databases identified 251 citations. After review of the titles, abstracts, and full articles, 7 met our inclusion and exclusion criteria.

RESULTS

Four studies assessed familial predisposition to rotator cuff disease. One of these demonstrated that siblings of an individual with a rotator cuff tear were more likely to develop a full-thickness tear and more likely to be symptomatic. A 5-year follow-up showed that the relative risks were increased for the siblings to have a full-thickness tear, for a tear to progress in size, and for being symptomatic. Another study demonstrated that a significantly higher number of individuals with tears had family members with a history of tears or surgery than those without tears did. The other 3 studies investigated whether a genetic predisposition to rotator cuff disease exists and found significant association of haplotypes in DEFB1, FGFR1, FGF3, ESRRB, and FGF10 and 2 single-nucleotide polymorphisms within SAP30BP and SASH1.

CONCLUSION

Prior studies provide preliminary evidence for genetic and familial predisposition to rotator cuff disease. However, there is a lack of large genome-wide studies that can provide more definitive information and guide early detection of individuals at risk, prophylactic rehabilitation, and potential gene therapies and regenerative medicine interventions.

Distinct Penetrance of Obesity-Associated Susceptibility Alleles in the Hungarian General and Roma Populations

AIMS

The aim of our study was to explore differences in genetic predisposition to obesity between the Hungarian general and Roma populations.

METHODS

A total of 1,152 samples from the Hungarian Roma population and 1,743 samples from the Hungarian general population were genotyped for 20 single nucleotide polymorphisms (SNPs) associated with the risk of obesity. Two types of multilocus genetic risk scores were constructed to estimate the combined effect of selected SNPs.

RESULTS

Risk allele frequencies differed significantly between the two populations for 11 SNPs, with no enrichment in any of the two study groups. Variants (rs1558902, rs1121980, rs9939609, and rs9941349) in the fat mass and obesity-associated (FTO) gene exhibited strong but ethnicity-independent association with obesity. Genetic risk scores showed stronger associations with obesity in the Roma population compared with the Hungarian general population; however, without significant gene-population interaction.

CONCLUSION

Differences in obesity prevalence between the Hungarian general and Hungarian Roma populations could not be explained by their distinct genetic susceptibility, rather by ethnicity-related environmental and behavioral factors. Nonetheless, particular gene-environment interactions might contribute to the distinct penetrance of the obesity-associated genetic factors in populations of different ethnic backgrounds.

Analysis of binary responses with outcome-specific misclassification probability in genome-wide association studies

Errors in the binary status of some response traits are frequent in human, animal, and plant applications. These error rates tend to differ between cases and controls because diagnostic and screening tests have different sensitivity and specificity. This increases the inaccuracies of classifying individuals into correct groups, giving rise to both false-positive and false-negative cases. The analysis of these noisy binary responses due to misclassification will undoubtedly reduce the statistical power of genome-wide association studies (GWAS). A threshold model that accommodates varying diagnostic errors between cases and controls was investigated. A simulation study was carried out where several binary data sets (case-control) were generated with varying effects for the most influential single nucleotide polymorphisms (SNPs) and different diagnostic error rate for cases and controls. Each simulated data set consisted of 2000 individuals. Ignoring misclassification resulted in biased estimates of true influential SNP effects and inflated estimates for true noninfluential markers. A substantial reduction in bias and increase in accuracy ranging from 12% to 32% was observed when the misclassification procedure was invoked. In fact, the majority of influential SNPs that were not identified using the noisy data were captured using the proposed method. Additionally, truly misclassified binary records were identified with high probability using the proposed method. The superiority of the proposed method was maintained across different simulation parameters (misclassification rates and odds ratios) attesting to its robustness.

Family-based association analyses of imputed genotypes reveal genome-wide significant association of Alzheimer's disease with OSBPL6, PTPRG, and PDCL3

The genetic basis of Alzheimer's disease (AD) is complex and heterogeneous. Over 200 highly penetrant pathogenic variants in the genes APP, PSEN1, and PSEN2 cause a subset of early-onset familial AD. On the other hand, susceptibility to late-onset forms of AD (LOAD) is indisputably associated to the ɛ4 allele in the gene APOE, and more recently to variants in more than two-dozen additional genes identified in the large-scale genome-wide association studies (GWAS) and meta-analyses reports. Taken together however, although the heritability in AD is estimated to be as high as 80%, a large proportion of the underlying genetic factors still remain to be elucidated. In this study, we performed a systematic family-based genome-wide association and meta-analysis on close to 15 million imputed variants from three large collections of AD families (~3500 subjects from 1070 families). Using a multivariate phenotype combining affection status and onset age, meta-analysis of the association results revealed three single nucleotide polymorphisms (SNPs) that achieved genome-wide significance for association with AD risk: rs7609954 in the gene PTPRG (P-value=3.98 × 10^-8), rs1347297 in the gene OSBPL6 (P-value=4.53 × 10^-8), and rs1513625 near PDCL3 (P-value=4.28 × 10^-8). In addition, rs72953347 in OSBPL6 (P-value=6.36 × 10^-7) and two SNPs in the gene CDKAL1 showed marginally significant association with LOAD (rs10456232, P-value=4.76 × 10^-7; rs62400067, P-value=3.54 × 10^-7). In summary, family-based GWAS meta-analysis of imputed SNPs revealed novel genomic variants in (or near) PTPRG, OSBPL6, and PDCL3 that influence risk for AD with genome-wide significance.

Evaluating the transferability of 15 European-derived fasting plasma glucose SNPs in Mexican children and adolescents

Genome wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with fasting plasma glucose (FPG) in adult European populations. The contribution of these SNPs to FPG in non-Europeans and children is unclear. We studied the association of 15 GWAS SNPs and a genotype score (GS) with FPG and 7 metabolic traits in 1,421 Mexican children and adolescents from Mexico City. Genotyping of the 15 SNPs was performed using TaqMan Open Array. We used multivariate linear regression models adjusted for age, sex, body mass index standard deviation score, and recruitment center. We identified significant associations between 3 SNPs (G6PC2 (rs560887), GCKR (rs1260326), MTNR1B (rs10830963)), the GS and FPG level. The FPG risk alleles of 11 out of the 15 SNPs (73.3%) displayed significant or non-significant beta values for FPG directionally consistent with those reported in adult European GWAS. The risk allele frequencies for 11 of 15 (73.3%) SNPs differed significantly in Mexican children and adolescents compared to European adults from the 1000G Project, but no significant enrichment in FPG risk alleles was observed in the Mexican population. Our data support a partial transferability of European GWAS FPG association signals in children and adolescents from the admixed Mexican population.

The ENPP1 K121Q polymorphism is associated with type 2 diabetes and related metabolic phenotypes in a Taiwanese population

Increased risk of developing type 2 diabetes (T2D) has been associated with a single nucleotide polymorphism (SNP), rs1044498 (K121Q), in the ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) gene, but this association is unclear among Asians. In this replication study, we reassessed whether the ENPP1 rs1044498 SNP is associated with T2D, obesity, and T2D/obesity-related metabolic traits in a Taiwanese population. A total of 1513 Taiwanese subjects were assessed in this study. The ENPP1 rs1044498 SNP was genotyped by the Taqman assay. T2D/Obesity-related quantitative traits, such as waist circumference and fasting glucose, were measured. Our data showed a significant association of the ENPP1 rs1044498 SNP with T2D (P < 0.001) among the subjects. Moreover, the ENPP1 rs1044498 SNP was significantly associated with T2D/obesity-related metabolic traits, such as waist circumference (P = 0.002) and fasting glucose (P < 0.001), among the subjects. However, we found no association of ENPP1 rs1044498 with obesity (BMI ≧ 27 kg/m(2)). Our study indicates that the ENPP1 rs1044498 SNP is associated with T2D, waist circumference, and fasting glucose in Taiwanese subjects.

Assessing the quality of published genetic association studies in meta-analyses: the quality of genetic studies (Q-Genie) tool

Background

Advances in genomics technology have led to a dramatic increase in the number of published genetic association studies. Systematic reviews and meta-analyses are a common method of synthesizing findings and providing reliable estimates of the effect of a genetic variant on a trait of interest. However, summary estimates are subject to bias due to the varying methodological quality of individual studies. We embarked on an effort to develop and evaluate a tool that assesses the quality of published genetic association studies. Performance characteristics (i.e. validity, reliability, and item discrimination) were evaluated using a sample of thirty studies randomly selected from a previously conducted systematic review.

Results

The tool demonstrates excellent psychometric properties and generates a quality score for each study with corresponding ratings of ‘low’, ‘moderate’, or ‘high’ quality. We applied our tool to a published systematic review to exclude studies of low quality, and found a decrease in heterogeneity and an increase in precision of summary estimates.

Conclusion

This tool can be used in systematic reviews to inform the selection of studies for inclusion, to conduct sensitivity analyses, and to perform meta-regressions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0211-2) contains supplementary material, which is available to authorized users.

Obesity genetics in mouse and human: back and forth, and back again

Obesity is a major public health concern. This condition results from a constant and complex interplay between predisposing genes and environmental stimuli. Current attempts to manage obesity have been moderately effective and a better understanding of the etiology of obesity is required for the development of more successful and personalized prevention and treatment options. To that effect, mouse models have been an essential tool in expanding our understanding of obesity, due to the availability of their complete genome sequence, genetically identified and defined strains, various tools for genetic manipulation and the accessibility of target tissues for obesity that are not easily attainable from humans. Our knowledge of monogenic obesity in humans greatly benefited from the mouse obesity genetics field. Genes underlying highly penetrant forms of monogenic obesity are part of the leptin-melanocortin pathway in the hypothalamus. Recently, hypothesis-generating genome-wide association studies for polygenic obesity traits in humans have led to the identification of 119 common gene variants with modest effect, most of them having an unknown function. These discoveries have led to novel animal models and have illuminated new biologic pathways. Integrated mouse-human genetic approaches have firmly established new obesity candidate genes. Innovative strategies recently developed by scientists are described in this review to accelerate the identification of causal genes and deepen our understanding of obesity etiology. An exhaustive dissection of the molecular roots of obesity may ultimately help to tackle the growing obesity epidemic worldwide.

Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals

Polymorphisms rs6232 and rs6234/rs6235 in PCSK1 have been associated with extreme obesity [e.g. body mass index (BMI) ≥ 40 kg/m(2)], but their contribution to common obesity (BMI ≥ 30 kg/m(2)) and BMI variation in a multi-ethnic context is unclear. To fill this gap, we collected phenotypic and genetic data in up to 331 175 individuals from diverse ethnic groups. This process involved a systematic review of the literature in PubMed, Web of Science, Embase and the NIH GWAS catalog complemented by data extraction from pre-existing GWAS or custom-arrays in consortia and single studies. We employed recently developed global meta-analytic random-effects methods to calculate summary odds ratios (OR) and 95% confidence intervals (CIs) or beta estimates and standard errors (SE) for the obesity status and BMI analyses, respectively. Significant associations were found with binary obesity status for rs6232 (OR = 1.15, 95% CI 1.06-1.24, P = 6.08 × 10(-6)) and rs6234/rs6235 (OR = 1.07, 95% CI 1.04-1.10, P = 3.00 × 10(-7)). Similarly, significant associations were found with continuous BMI for rs6232 (β = 0.03, 95% CI 0.00-0.07; P = 0.047) and rs6234/rs6235 (β = 0.02, 95% CI 0.00-0.03; P = 5.57 × 10(-4)). Ethnicity, age and study ascertainment significantly modulated the association of PCSK1 polymorphisms with obesity. In summary, we demonstrate evidence that common gene variation in PCSK1 contributes to BMI variation and susceptibility to common obesity in the largest known meta-analysis published to date in genetic epidemiology.

The genetic variants underlying breast cancer treatment-induced chronic and late toxicities: a systematic review

A systematic review was performed to describe the findings from 19 genetic association studies that have examined the genetic variants underlying four common treatment-induced chronic and late toxicities in breast cancer patients, and to evaluate the quality of reporting. Three out of 5 studies found an association between HER2 lle655Val polymorphisms and trastuzumab-induced cardiotoxicity. Two studies found a positive association between cognitive impairment and the Val allele of the COMT gene and the ε4 allele of the apolipoprotein E gene. Genetic associations were established between fatigue and the G/G genotype of IL6-174 and TNF-308, and the Met allele of the COMT gene in 4 studies. Among studies (N=8) that evaluated the genetic associations underlying peripheral neuropathy, CYP2C8∗3 variant is commonly reported as the associated gene. Most studies failed to conform to the major criteria listed in the STREGA guidelines, with a lack of transparent reporting of methods and results.

Jumping on the Train of Personalized Medicine: A Primer for Non-Geneticist Clinicians: Part 2. Fundamental Concepts in Genetic Epidemiology

With the decrease in sequencing costs, personalized genome sequencing will eventually become common in medical practice. We therefore write this series of three reviews to help non-geneticist clinicians to jump into the fast-moving field of personalized medicine. In the first article of this series, we reviewed the fundamental concepts in molecular genetics. In this second article, we cover the key concepts and methods in genetic epidemiology including the classification of genetic disorders, study designs and their implementation, genetic marker selection, genotyping and sequencing technologies, gene identification strategies, data analyses and data interpretation. This review will help the reader critically appraise a genetic association study. In the next article, we will discuss the clinical applications of genetic epidemiology in the personalized medicine area.

Mutations in Ovis aries TMEM154 are associated with lower small ruminant lentivirus proviral concentration in one sheep flock

Small ruminant lentivirus (SRLV), also called ovine progressive pneumonia virus or maedi-visna, is present in 24% of US sheep. Like human immunodeficiency virus, SRLV is a macrophage-tropic lentivirus that causes lifelong infection. The production impacts from SRLV are due to a range of disease symptoms, including pneumonia, arthritis, mastitis, body condition wasting and encephalitis. There is no cure and no effective vaccine for preventing SRLV infection. However, breed differences in prevalence and proviral concentration indicate a genetic basis for susceptibility to SRLV. Animals with high blood proviral concentration show increased tissue lesion severity, so proviral concentration represents a live animal test for control post-infection in terms of proviral replication and disease severity. Recently, it was found that sheep with two copies of TMEM154 haplotype 1 (encoding lysine at position 35) had lower odds of SRLV infection. In this study, we examined the relationship between SRLV control post-infection and variants in two genes, TMEM154 and CCR5, in four flocks containing 1403 SRLV-positive sheep. We found two copies of TMEM154 haplotype 1 were associated with lower SRLV proviral concentration in one flock (P < 0.02). This identified the same favorable diplotype for SRLV control post-infection as for odds of infection. However, frequencies of haplotypes 2 and 3 were too low in the other three flocks to test. The CCR5 promoter deletion did not have consistent association with SRLV proviral concentration. Future work in flocks with more balanced allele frequencies is needed to confirm or refute TMEM154 association with control of SRLV post-infection.

Genome wide association studies in presence of misclassified binary responses

BACKGROUND

Misclassification has been shown to have a high prevalence in binary responses in both livestock and human populations. Leaving these errors uncorrected before analyses will have a negative impact on the overall goal of genome-wide association studies (GWAS) including reducing predictive power. A liability threshold model that contemplates misclassification was developed to assess the effects of mis-diagnostic errors on GWAS. Four simulated scenarios of case-control datasets were generated. Each dataset consisted of 2000 individuals and was analyzed with varying odds ratios of the influential SNPs and misclassification rates of 5% and 10%.

RESULTS

Analyses of binary responses subject to misclassification resulted in underestimation of influential SNPs and failed to estimate the true magnitude and direction of the effects. Once the misclassification algorithm was applied there was a 12% to 29% increase in accuracy, and a substantial reduction in bias. The proposed method was able to capture the majority of the most significant SNPs that were not identified in the analysis of the misclassified data. In fact, in one of the simulation scenarios, 33% of the influential SNPs were not identified using the misclassified data, compared with the analysis using the data without misclassification. However, using the proposed method, only 13% were not identified. Furthermore, the proposed method was able to identify with high probability a large portion of the truly misclassified observations.

CONCLUSIONS

The proposed model provides a statistical tool to correct or at least attenuate the negative effects of misclassified binary responses in GWAS. Across different levels of misclassification probability as well as odds ratios of significant SNPs, the model proved to be robust. In fact, SNP effects, and misclassification probability were accurately estimated and the truly misclassified observations were identified with high probabilities compared to non-misclassified responses. This study was limited to situations where the misclassification probability was assumed to be the same in cases and controls which is not always the case based on real human disease data. Thus, it is of interest to evaluate the performance of the proposed model in that situation which is the current focus of our research.

Lack of association between DRD2 and OPRM1 genotypes and adiposity

BACKGROUND

Dopaminergic and opioid systems are both involved in food intake and appetite control. The dopamine D2 receptor gene (DRD2) and the μ-opioid receptor gene (OPRM1) therefore represent plausible candidates for association with obesity.

OBJECTIVE

Previous studies of these variants have yielded inconsistent findings, which are likely due to insufficient statistical power. The aim of the current study was to determine whether, in a large population-based sample, there are associations between adiposity and (i) the A1 (T) allele of the Taq1A polymorphism (rs1800497) in DRD2 and (ii) the G allele of the A118G polymorphism (rs1799971) in OPRM1.

STUDY POPULATION

Annual clinic-based measures of body mass index (BMI) and waist circumference were taken from children (N=3720) at 5 measurement time points from ages 7 through to 11 years. BMI was also recorded in their mothers (N=2460) at comparable time points and at pre-pregnancy. All participants were genotyped. Our study was powered (at 80%) to detect per-allele effects on BMI of 0.21 kg m(-2).

RESULTS

Our results indicate a lack of association between DRD2 and OPRM1 genotypes and adiposity. Combining the data across mothers and children found per-allele effects on BMI of 0.02 kg m(-2) (95% confidence interval (CI): -0.17, 0.20), P=0.9 for rs1800497 and -0.08 kg m(-2) (95% CI: -0.29, 0.22), P=0.4 for rs1799971. As a positive control, we also examined the effect of FTO genotype over the same time period and confirmed the expected relationship between variability at this locus and higher adiposity.

CONCLUSION

Our findings question existing evidence suggesting associations at DRD2 and OPRM1 loci and adiposity. They also highlight the caution required when employing candidate gene approaches to further our understanding of the neurobiology of eating and obesity.

Genetics of obesity and type 2 diabetes in African Americans

Obesity and type 2 diabetes are highly prevalent and lead to significant morbidity and mortality. In the United States, the impact of these conditions may be worse on historically underserved minorities, particularly African Americans. Genetic ancestry and differences in physiology are unlikely to be the sole or primary determinants of these disparities. In addition, research in this area has the ethically problematic possibility of conflating race with biology. Despite these important considerations and the challenges of conducting this work, population-based approaches for investigating the etiology of obesity and T2D may yield useful information about the pathophysiology of disease, and have implications that extend to all affected individuals. The purpose of this paper is to describe what is understood about the genetic variation that underlies obesity and T2D in African Americans and other individuals of more recent African descent and to highlight several examples that illustrate how ensuring adequate minority representation in genetic research improves its quality. For a variety of reasons a number of unique insights have been possible as a result of these efforts.