The humankind genome: from genetic diversity to the origin of human diseases

Genome ◽  
2013 ◽  
Vol 56 (12) ◽  
pp. 705-716 ◽  
Author(s):  
Jose E. Belizário
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Model Organism ◽  
Copy Number Variations ◽  
Genomic Variation ◽  
Human Diseases ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Full Characterization ◽  
Sequencing Technologies

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease’s etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

scholarly journals Assessing the Causal Effects of Human Serum Metabolites on 5 Major Psychiatric Disorders

2020 ◽  
Vol 46 (4) ◽  
pp. 804-813 ◽  
Author(s):  
Jian Yang ◽  
Bin Yan ◽  
Binbin Zhao ◽  
Yajuan Fan ◽  
Xiaoyan He ◽  
...  
Keyword(s):  
Human Serum ◽  
Psychiatric Disorders ◽  
Genetic Variants ◽  
Association Studies ◽  
Autism Spectrum ◽  
Causal Effects ◽  
Human Diseases ◽  
Genome Wide Association Studies ◽  
Serum Metabolites ◽  
Intermediate Phenotypes

Abstract Psychiatric disorders are the leading cause of disability worldwide while the pathogenesis remains unclear. Genome-wide association studies (GWASs) have made great achievements in detecting disease-related genetic variants. However, functional information on the underlying biological processes is often lacking. Current reports propose the use of metabolic traits as functional intermediate phenotypes (the so-called genetically determined metabotypes or GDMs) to reveal the biological mechanisms of genetics in human diseases. Here we conducted a two-sample Mendelian randomization analysis that uses GDMs to assess the causal effects of 486 human serum metabolites on 5 major psychiatric disorders, which respectively were schizophrenia (SCZ), major depression (MDD), bipolar disorder (BIP), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD). Using genetic variants as proxies, our study has identified 137 metabolites linked to the risk of psychiatric disorders, including 2-methoxyacetaminophen sulfate, which affects SCZ (P = 1.7 × 10–5) and 1-docosahexaenoylglycerophosphocholine, which affects ADHD (P = 5.6 × 10–5). Fourteen significant metabolic pathways involved in the 5 psychiatric disorders assessed were also detected, such as glycine, serine, and threonine metabolism for SCZ (P = .0238), Aminoacyl-tRNA biosynthesis for both MDD (P = .0144) and ADHD (P = .0029). Our study provided novel insights into integrating metabolomics with genomics in order to understand the mechanisms underlying the pathogenesis of human diseases.

PL01-01 - Genetic Reseach: Promises and Pitfalls for Clinical Treatment of Depression

2011 ◽  
Vol 26 (S2) ◽  
pp. 2007-2007
Author(s):  
J. Mendlewicz
Keyword(s):  
Mood Disorders ◽  
Genetic Variants ◽  
Rare Variants ◽  
Association Studies ◽  
Copy Number Variations ◽  
Depressive Illness ◽  
Public Health Issue ◽  
Genome Wide Association Studies ◽  
Structural Variations ◽  
Epigenetic Modulation

The lifetime prevalence of mood disorders is estimated around 20% in the general population leading to a main cause of disability worldwide and a major public health issue.1 The ethiology of mood disorders is still unknown, but its various phenotypes are believed to be caused by multiple genetic variants interacting in a complex way with environmental vulnerability factors. Therefore, the identification of biomarkers and environmental markers is crucial to improve our understanding and diagnosis as well as our treatments. Despite intensive and costly research for more than two decades to unravel suceptibility genes, although pathophysiological pathways of interest have been recongnized, results have not been consistant so far and not a single genetic biomarker of depression has been identified and replicated. More recent systematic genome-wide association studies (GWAS) have reported weak associations of some genetic variants in large samples, but multiple rare variants may concur to confer only part of the suceptibility to depression. Structural variations may also be considered to be promising as is the case for copy-number-variations (CNVs). Methodological issues and limitations will also be critically discussed in light of the complexity of gene-evironment interactions (epigenetic modulation of gene expression)2 and in relation to future prospects for individualized pharmacotherapy of depressive illness.

scholarly journals Lipid associated polygenic enrichment in Alzheimer’s disease

2018 ◽  
Author(s):  
Iris J. Broce ◽  
Chin Hong Tan ◽  
Chun Chieh Fan ◽  
Aree Witoelar ◽  
Natalie Wen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Variants ◽  
Plasma Lipids ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genetic Pleiotropy ◽  
Common Genetic Variants

ABSTRACTCardiovascular (CV) and lifestyle associated risk factors (RFs) are increasingly recognized as important for Alzheimer’s disease (AD) pathogenesis. Beyond the ∊4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV associated genes also increase risk for AD (genetic pleiotropy). Using large genome-wide association studies (GWASs) (total n > 500,000 cases and controls) and validated tools to quantify genetic pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 57 SNPs on 19 different chromosomes that were jointly associated with AD and CV outcomes including APOA4, ABCA1, ABCG5, LIPG, and MTCH2/SPI1. We found that common genetic variants influencing AD are associated with multiple CV RFs, at times with a different directionality of effect. Expression of these AD/CV pleiotropic genes was enriched for lipid metabolism processes, over-represented within astrocytes and vascular structures, highly co-expressed, and differentially altered within AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid associated RFs. Rather than a single causal link between genetic loci, RF and the outcome, we found that common genetic variants influencing AD are associated with multiple CV RFs. Our collective findings suggest that a network of genes involved in lipid biology also influence Alzheimer’s risk.

scholarly journals Polygenic risk score based on weight gain trajectories is predictive of childhood obesity

2019 ◽  
Author(s):  
Sarah J. C. Craig ◽  
Ana M. Kenney ◽  
Junli Lin ◽  
Ian M. Paul ◽  
Leann L. Birch ◽  
...  
Keyword(s):  
Weight Gain ◽  
Childhood Obesity ◽  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide

AbstractObesity is highly heritable, yet only a small fraction of its heritability has been attributed to specific genetic variants. These variants are traditionally ascertained from genome-wide association studies (GWAS), which utilize samples with tens or hundreds of thousands of individuals for whom a single summary measurement (e.g., BMI) is collected. An alternative approach is to focus on a smaller, more deeply characterized sample in conjunction with advanced statistical models that leverage detailed phenotypes. Here we use novel functional data analysis (FDA) techniques to capitalize on longitudinal growth information and construct a polygenic risk score (PRS) for obesity in children followed from birth to three years of age. This score, comprised of 24 single nucleotide polymorphisms (SNPs), is significantly higher in children with (vs. without) rapid infant weight gain—a predictor of obesity later in life. Using two independent cohorts, we show that genetic variants identified in early childhood are also informative in older children and in adults, consistent with early childhood obesity being predictive of obesity later in life. In contrast, PRSs based on SNPs identified by adult obesity GWAS are not predictive of weight gain in our cohort of children. Our research provides an example of a successful application of FDA to GWAS. We demonstrate that a deep, statistically sophisticated characterization of a longitudinal phenotype can provide increased statistical power to studies with relatively small sample sizes. This study shows how FDA approaches can be used as an alternative to the traditional GWAS.Author SummaryFinding genetic variants that confer an increased risk of developing a particular disease has long been a focus of modern genetics. Genome wide association studies (GWAS) have catalogued single nucleotide polymorphisms (SNPs) associated with a variety of complex diseases in humans, including obesity, but by and large have done so using increasingly large samples-- tens or even hundreds of thousands of individuals, whose phenotypes are thus often only superficially characterized. This, in turn, may hide the intricacies of the genetic influence on disease. GWAS findings are also usually study-population dependent. We found that genetic risk scores based on SNPs from large adult obesity studies are not predictive of the propensity to gain weight in very young children. However, using a small cohort of a few hundred children deeply characterized with growth trajectories between birth and two years, and leveraging such trajectories through novel functional data analysis (FDA) techniques, we were able to produce a strong childhood obesity genetic risk score.

scholarly journals Puberty Status Modifies the Effects of Genetic Variants, Lifestyle Factors and Their Interactions on Adiponectin: The BCAMS Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Yunpeng Wu ◽  
Ling Zhong ◽  
Ge Li ◽  
Lanwen Han ◽  
Junling Fu ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Pubertal Development ◽  
Lifestyle Factors ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Exercise Frequency ◽  
Cross Sectional ◽  
Individual Snps ◽  
Diet Score

BackgroundHypoadiponectinemia has been associated with various cardiometabolic disease states. Previous studies in adults have shown that adiponectin levels were regulated by specific genetic and behavioral or lifestyle factors. However, little is known about the influence of these factors on adiponectin levels in children, particularly as mitigated by pubertal development.MethodsWe performed a cross-sectional analysis of data from 3,402 children aged 6-18 years from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS) study. Pubertal progress was classified as prepubertal, midpuberty, and postpuberty. Six relevant single nucleotide polymorphisms (SNPs) were selected from previous genome-wide association studies of adiponectin in East Asians. Individual SNPs and two weighted genetic predisposition scores, as well as their interactions with 14 lifestyle factors, were analyzed to investigate their influence on adiponectin levels across puberty. The effect of these factors on adiponectin was analyzed using general linear models adjusted for age, sex, and BMI.ResultsAfter adjustment for age, sex, and BMI, the associations between adiponectin levels and diet items, and diet score were significant at prepuberty or postpuberty, while the effect of exercise on adiponectin levels was more prominent at mid- and postpuberty. Walking to school was found to be associated with increased adiponectin levels throughout puberty. Meanwhile, the effect of WDR11-FGFR2-rs3943077 was stronger at midpuberty (P = 0.002), and ADIPOQ-rs6773957 was more effective at postpuberty (P = 0.005), while CDH13-rs4783244 showed the strongest association with adiponectin levels at all pubertal stages (all P &lt; 3.24 × 10-15). We further found that effects of diet score (Pinteraction = 0.022) and exercise (Pinteraction = 0.049) were stronger in children with higher genetic risk of hypoadiponectinemia, while higher diet score and exercise frequency attenuated the differences in adiponectin levels among children with different genetic risks.ConclusionsOur study confirmed puberty modulates the associations between adiponectin, and genetic variants, lifestyle factors, and gene-by-lifestyle interactions. These findings provide new insight into puberty-specific lifestyle suggestions, especially in genetically susceptible individuals.

scholarly journals Unravelling the Roles Of susceptibility Loci for Autoimmune Diseases in the Post-GWAS Era

2018 ◽  
Author(s):  
Jody Ye ◽  
Kathleen Gillespie ◽  
Santiago Rodriguez
Keyword(s):  
Autoimmune Diseases ◽  
Disease Risk ◽  
Association Studies ◽  
Copy Number Variations ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Susceptibility Loci ◽  
Single Nucleotide ◽  
Environmental Interactions ◽  
Genome Wide

Although genome-wide association studies (GWAS) have identified several hundred loci associated with autoimmune diseases, their mechanistic insights are still poorly understood. The human genome is more complex than common single nucleotide polymorphisms (SNPs) that are interrogated by GWAS arrays. Some structural variants such as insertions-deletions, copy number variations, and minisatellites that are not very well tagged by SNPs cannot be fully explored by GWAS. Therefore, it is possible that some of these loci may have large effects on autoimmune disease risk. In addition, other layers of regulations such as gene-gene interactions, epigenetic-determinants, gene and environmental interactions also contribute to the heritability of autoimmune diseases. This review focuses on discussing why studying these elements may allow us to gain a more comprehensive understanding of the aetiology of complex autoimmune traits.

scholarly journals Genetic Variants Shaping Inter-individual Differences in Response to Dietary Intakes—A Narrative Review of the Case of Vitamins

2020 ◽  
Vol 7 ◽  
Author(s):  
Aikaterini Niforou ◽  
Valentini Konstantinidou ◽  
Androniki Naska
Keyword(s):  
Vitamin D ◽  
Vitamin C ◽  
Genetic Variants ◽  
Current Knowledge ◽  
Association Studies ◽  
Genetic Variations ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Dietary Intakes ◽  
Genes Encoding

Recent advances in the field of nutrigenetics have provided evidence on how genetic variations can impact the individuals' response to dietary intakes. An objective and reliable assessment of dietary exposures should rely on combinations of methodologies including frequency questionnaires, short-term recalls or records, together with biological samples to evaluate markers of intake or status and to identify genetic susceptibilities. In an attempt to present current knowledge on how genetic fingerprints contribute to an individual's nutritional status, we present a review of current literature describing associations between genetic variants and levels of well-established biomarkers of vitamin status in free-living and generally healthy individuals. Based on the outcomes of candidate gene, genome-wide-association studies and meta-analyses thereof, we have identified several single nucleotide polymorphisms (SNPs) involved in the vitamins' metabolic pathways. Polymorphisms in genes encoding proteins involved in vitamin metabolism and transport are reported to have an impact on vitamin D status; while genetic variants of vitamin D receptor were most frequently associated with health outcomes. Genetic variations that can influence vitamin E status include SNPs involved in its uptake and transport, such as in SCAR-B1 gene, and in lipoprotein metabolism. Variants of the genes encoding the sodium-dependent vitamin C transport proteins are greatly associated with the body's status on vitamin C. Regarding the vitamins of the B-complex, special reference is made to the widely studied variant in the MTHFR gene. Methodological attributes of genetic studies that may limit the comparability and interpretability of the findings are also discussed. Our understanding of how genes affect our responses to nutritional triggers will enhance our capacity to evaluate dietary exposure and design personalized nutrition programs to sustain health and prevent disease.

scholarly journals Genetic Variants behind Cardiovascular Diseases and Dementia

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1514
Author(s):  
Wei-Min Ho ◽  
Yah-Yuan Wu ◽  
Yi-Chun Chen
Keyword(s):  
White Matter ◽  
Cardiovascular Diseases ◽  
Genetic Variants ◽  
White Matter Hyperintensities ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genetic Associations ◽  
Pubmed Database ◽  
Risk Snps

Cardiovascular diseases (CVDs) and dementia are the leading causes of disability and mortality. Genetic connections between cardiovascular risk factors and dementia have not been elucidated. We conducted a scoping review and pathway analysis to reveal the genetic associations underlying both CVDs and dementia. In the PubMed database, literature was searched using keywords associated with diabetes mellitus, hypertension, dyslipidemia, white matter hyperintensities, cerebral microbleeds, and covert infarctions. Gene lists were extracted from these publications to identify shared genes and pathways for each group. This included high penetrance genes and single nucleotide polymorphisms (SNPs) identified through genome wide association studies. Most risk SNPs to both diabetes and dementia participate in the phospholipase C enzyme system and the downstream nositol 1,4,5-trisphosphate and diacylglycerol activities. Interestingly, AP-2 (TFAP2) transcription factor family and metabolism of vitamins and cofactors were associated with genetic variants that were shared by white matter hyperintensities and dementia, and by microbleeds and dementia. Variants shared by covert infarctions and dementia were related to VEGF ligand–receptor interactions and anti-inflammatory cytokine pathways. Our review sheds light on future investigations into the causative relationships behind CVDs and dementia, and can be a paradigm of the identification of dementia treatments.

scholarly journals Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population

2018 ◽  
Vol 50 (3) ◽  
pp. 179-189 ◽  
Author(s):  
Yoshiki Yasukochi ◽  
Jun Sakuma ◽  
Ichiro Takeuchi ◽  
Kimihiko Kato ◽  
Mitsutoshi Oguri ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Genetic Variants ◽  
Japanese Population ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Susceptibility Loci ◽  
Cross Sectional ◽  
Japanese Subjects

Recent genome-wide association studies have identified various obesity or metabolic syndrome (MetS) susceptibility loci. However, most studies were conducted in a cross-sectional manner. To address this gap, we performed a longitudinal exome-wide association study to identify susceptibility loci for obesity and MetS in a Japanese population. We traced clinical data of 6,022 Japanese subjects who had annual health check-ups for several years (mean follow-up period, 5 yr) and genotyped ~244,000 genetic variants. The association of single nucleotide polymorphisms (SNPs) with body mass index (BMI) or the prevalence of obesity and MetS was examined in a generalized estimating equation model. Our longitudinal exome-wide association studies detected 21 BMI- and five MetS-associated SNPs (false discovery rate, FDR <0.01). Among these SNPs, 16 have not been previously implicated as determinants of BMI or MetS. Cross-sectional data for obesity- and MetS-related phenotypes in 7,285 Japanese subjects were examined in a replication study. Among the 16 SNPs, three ( rs9491140 , rs145848316 , and rs7863248 ) were related to BMI in the replication cohort ( P < 0.05). In conclusion, three SNPs [ rs9491140 of NKAIN2 (FDR = 0.003, P = 1.9 × 10−5), rs145848316 of KMT2C (FDR = 0.007, P = 4.5 × 10−5), and rs7863248 of AGTPBP1 (FDR = 0.006, P = 4.2 × 10−5)] were newly identified as susceptibility loci for BMI.

scholarly journals Genetic-variant hotspots and hotspot clusters in the human genome facilitating adaptation while increasing instability

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Xi Long ◽  
Hong Xue
Keyword(s):  
Human Genome ◽  
Genetic Variants ◽  
Complex Traits ◽  
Genetic Variant ◽  
Phenotypic Diversity ◽  
Association Studies ◽  
Copy Number Variations ◽  
Receptor Interaction ◽  
Common Disease ◽  
Nucleotide Polymorphisms

Abstract Background Genetic variants, underlining phenotypic diversity, are known to distribute unevenly in the human genome. A comprehensive understanding of the distributions of different genetic variants is important for insights into genetic functions and disorders. Methods Herein, a sliding-window scan of regional densities of eight kinds of germline genetic variants, including single-nucleotide-polymorphisms (SNPs) and four size-classes of copy-number-variations (CNVs) in the human genome has been performed. Results The study has identified 44,379 hotspots with high genetic-variant densities, and 1135 hotspot clusters comprising more than one type of hotspots, accounting for 3.1% and 0.2% of the genome respectively. The hotspots and clusters are found to co-localize with different functional genomic features, as exemplified by the associations of hotspots of middle-size CNVs with histone-modification sites, work with balancing and positive selections to meet the need for diversity in immune proteins, and facilitate the development of sensory-perception and neuroactive ligand-receptor interaction pathways in the function-sparse late-replicating genomic sequences. Genetic variants of different lengths co-localize with retrotransposons of different ages on a “long-with-young” and “short-with-all” basis. Hotspots and clusters are highly associated with tumor suppressor genes and oncogenes (p < 10−10), and enriched with somatic tumor CNVs and the trait- and disease-associated SNPs identified by genome-wise association studies, exceeding tenfold enrichment in clusters comprising SNPs and extra-long CNVs. Conclusions In conclusion, the genetic-variant hotspots and clusters represent two-edged swords that spearhead both positive and negative genomic changes. Their strong associations with complex traits and diseases also open up a potential “Common Disease-Hotspot Variant” approach to the missing heritability problem.

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