Genome wide association studies (GWAS) have focused on elucidating the genetic architecture of complex traits by assessing single variant effects in additive genetic models, albeit explaining a ...fraction of the trait heritability. Epistasis has recently emerged as one of the intrinsic mechanisms that could explain part of this missing heritability. We conducted epistasis analysis for genome-wide body mass index (BMI) associated SNPs in Alzheimer's Disease Neuroimaging Initiative (ADNI) and followed up top significant interacting SNPs for replication in the UK Biobank imputed genotype dataset. We report two pairwise epistatic interactions, between rs2177596 (RHBDD1) and rs17759796 (MAPK1), rs1121980 (FTO) and rs6567160 (MC4R), obtained from a consensus of nine different epistatic approaches. Gene interaction maps and tissue expression profiles constructed for these interacting loci highlights co-expression, co-localisation, physical interaction, genetic interaction, and shared pathways emphasising the neuronal influence in obesity and implicating concerted expression of associated genes in liver, pancreas, and adipose tissues insinuating to metabolic abnormalities characterized by obesity. Detecting epistasis could thus be a promising approach to understand the effect of simultaneously interacting multiple genetic loci in disease aetiology, beyond single locus effects.
Cognitive functioning is heritable, with metabolic risk factors known to accelerate age-associated cognitive decline. Identifying genetic underpinnings of cognition is thus crucial. Here, we ...undertake single-variant and gene-based association analyses upon 6 neurocognitive phenotypes across 6 cognition domains in whole-exome sequencing data from 157,160 individuals of the UK Biobank cohort to expound the genetic architecture of human cognition. We report 20 independent loci associated with 5 cognitive domains while controlling for APOE isoform-carrier status and metabolic risk factors; 18 of which were not previously reported, and implicated genes relating to oxidative stress, synaptic plasticity and connectivity, and neuroinflammation. A subset of significant hits for cognition indicates mediating effects via metabolic traits. Some of these variants also exhibit pleiotropic effects on metabolic traits. We further identify previously unknown interactions of APOE variants with LRP1 (rs34949484 and others, suggestively significant), AMIGO1 (rs146766120; pAla25Thr, significant), and ITPR3 (rs111522866, significant), controlling for lipid and glycemic risks. Our gene-based analysis also suggests that APOC1 and LRP1 have plausible roles along shared pathways of amyloid beta (Aβ) and lipid and/or glucose metabolism in affecting complex processing speed and visual attention. In addition, we report pairwise suggestive interactions of variants harbored in these genes with APOE affecting visual attention. Our report based on this large-scale exome-wide study highlights the effects of neuronal genes, such as LRP1, AMIGO1, and other genomic loci, thus providing further evidence of the genetic underpinnings for cognition during aging.
Exome-wide association study in >150,000 individuals identifies LRP1, AMIGO1, APOC1, and additional genetic loci acting in conjunction with APOE, revealing genetic underpinnings of 5 domains of cognition, in the presence of age-associated metabolic risks, for example, dyslipidemia and glycemic imbalance. These variants regulate expression of associated genes in cerebellum and cortex.
Introduction
An extensive battery of neuropsychological tests is currently used to classify individuals as healthy (HV), mild cognitively impaired (MCI), and with Alzheimer's disease (AD). We used ...machine learning models for effective cognitive impairment classification and optimized the number of tests for expeditious and inexpensive implementation.
Methods
Using random forests (RF) and support vector machine, we classified cognitive impairment in multi‐class data sets from Rush Religious Orders Study Memory and Aging Project, and National Alzheimer's Coordinating Center. We applied Fisher's linear discrimination and assessed importance of each test iteratively for feature selection.
Results
RF has best accuracy with increased sensitivity, specificity in this first ever multi‐class classification of HV, MCI, and AD. Moreover, a subset of six to eight tests shows equivalent classification accuracy as an entire battery of tests.
Discussions
Fully automated feature selection approach reveals six to eight tests comprising episodic, semantic memory, perceptual orientation, and executive functioning can accurately classify the cognitive status, ensuring minimal subject burden.
Structural variations (SV) are large (>50 base pairs) genomic rearrangements comprising deletions, duplications, insertions, inversions, and translocations. Studying SVs is important because they ...play active and critical roles in regulating gene expression, determining disease predispositions, and identifying population-specific differences among individuals of diverse ancestries. However, SV discoveries in the Indian population using whole-genome sequencing (WGS) have been limited. In this study, using short-read WGS having an average 42X depth of coverage, we identify and characterize 36,210 SVs from 529 individuals enrolled in population-based cohorts in India. These SVs include 24,574 deletions, 2,913 duplications, 8,710 insertions, and 13 inversions; 1.26% (456 out of 36,210) of the identified SVs can potentially impact the coding regions of genes. Furthermore, 56 of these SVs are highly intolerant to loss-of-function changes to the mapped genes, and five SVs impacting ADAMTS17, CCDC40, and RHCE are common in our study individuals. Seven rare SVs significantly impact dosage sensitivity of genes known to be associated with various clinical phenotypes. Most of the SVs in our study are rare and heterozygous. This fine-scale SV discovery in the underrepresented Indian population provides valuable insights that extend beyond Eurocentric human genetic studies.
Whole-genome sequencing in 529 individuals from population-based Indian cohorts reveal 36,210 structural variations (SVs), including deletions, duplications, and insertions; 1.26% of SVs can impact gene coding regions, with 56 highly intolerant to loss-of-function changes. This study provides valuable insights into underrepresented Indian populations, extending beyond Eurocentric genetic studies.
Nonalcoholic fatty liver disease (NAFLD) is an obesity‐related condition affecting over 50% of individuals in some populations and is expected to become the number one cause of liver disease ...worldwide by 2020. Common, robustly associated genetic variants in/near five genes were identified for hepatic steatosis, a quantifiable component of NAFLD, in European ancestry individuals. Here we tested whether these variants were associated with hepatic steatosis in African‐ and/or Hispanic‐Americans and fine‐mapped the observed association signals. We measured hepatic steatosis using computed tomography in five African American (n = 3,124) and one Hispanic American (n = 849) cohorts. All analyses controlled for variation in age, age2, gender, alcoholic drinks, and population substructure. Heritability of hepatic steatosis was estimated in three cohorts. Variants in/near PNPLA3, NCAN, LYPLAL1, GCKR, and PPP1R3B were tested for association with hepatic steatosis using a regression framework in each cohort and meta‐analyzed. Fine‐mapping across African American cohorts was conducted using meta‐analysis. African‐ and Hispanic‐American cohorts were 33.9/37.5% male, with average age of 58.6/42.6 years and body mass index of 31.8/28.9 kg/m2, respectively. Hepatic steatosis was 0.20‐0.34 heritable in African‐ and Hispanic‐American families (P < 0.02 in each cohort). Variants in or near PNPLA3, NCAN, GCKR, PPP1R3B in African Americans and PNPLA3 and PPP1R3B in Hispanic Americans were significantly associated with hepatic steatosis; however, allele frequency and effect size varied across ancestries. Fine‐mapping in African Americans highlighted missense variants at PNPLA3 and GCKR and redefined the association region at LYPLAL1. Conclusion: Multiple genetic variants are associated with hepatic steatosis across ancestries. This explains a substantial proportion of the genetic predisposition in African‐ and Hispanic‐Americans. Missense variants in PNPLA3 and GCKR are likely functional across multiple ancestries. (Hepatology 2013;53:966–975)
Whole Genome Sequencing (WGS) provides information for each base of the entire 3.2 billion base pairs of the diploid human genome. Therefore, WGS plays an important role in identifying genetic ...variations for populations and understanding disease signatures in cohort studies or cases with rare genetic disorders. Nonetheless, discoveries from high throughput WGS are dependent on efficient processing, analyzing, and storing this enormous amount of genomic sequencing data, often in the scale of petabytes. Although there has been a significant reduction in genome sequencing costs in recent years, high-performance computation costs have not decreased in a directly proportional fashion.
The objective of the present work is to develop a Docker-based container method for human whole genome sequencing data processing and analysis for detecting genetic variations from paired end WGS short reads. Our method provides an approach to simultaneously process multiple genomes within a single compute system while guaranteeing sustained and stable handling of the memory requirements for the genomic data processing and ensuring no unwanted termination of the currently running parallel jobs. This method also achieves a 40 % reduction in execution time. To encourage widespread adoption and ease of WGS analysis, our containerized pipeline will be made publicly available. We have tested this approach for human genome data from Illumina WGS platforms and report the benchmark metrics in two different workstation environments in this communication. Compared to truth sets, our approach calls variants with 99 % precision and recall.
Background
Addenbrooke’s Cognitive Examination (ACE‐III) is a well‐validated cognitive screening test, designed to detect Dementia. This work intends to investigate the influence of age, gender, and ...education in Indian population.
Method
Srinivaspura Aging, Neuro Senescence and COGnition (SANSCOG) study and Tata Longitudinal Study on Aging (TLSA) are parallel, prospective, community‐based, cohort studies in India – rural and urban respectively – for comprehensive evaluation of risk and protective factors associated with cognitive changes due to normal ageing, Alzheimer’s disease and other related disorders. 444 and 1344 volunteers were enrolled in TLSA and SANSCOG respectively. ACE‐III was administered on them by trained psychologists. They were classified in four age groups (45– 55, 56–65, 66‐75, and >75 years of age) and six levels for years of education (0‐4, 5‐8, 9‐12, 13‐15, 16‐18, >18). Univariate analysis was performed to study the effect of age, gender, or education, on the ACE‐III total scores. Multivariate analysis was done to study the effects of age, gender, and education on the different cognitive domains of ACE‐III.
Result
No significant differences were observed for ACE‐III among different age groups or gender for individuals enrolled in TLSA, as well as those in SANSCOG. The level of education had a significant effect on ACE‐III as well as all the sub‐domains for SANSCOG participants, but not for TLSA participants. However, age or gender do not show such trends. When the effect of age, gender, and level of education was jointly assessed on these indices, they were found to have significant effects only for visuospatial domain for TLSA participants; and attention and visuospatial domain for SANSCOG participants. Additionally, memory, fluency, language, visuospatial indices of ACE‐III are significantly affected by the age of the participant in SANSCOG.
Conclusion
These results show that age, gender and education of participants can have important effects on performance of ACE‐III and its cognitive sub‐domains. Nevertheless, this is an ongoing work, and currently more participants are being assessed in both the studies who would be followed up longitudinally, which can yield precise conclusive results in future.
Abstract
Background
Addenbrooke’s Cognitive Examination (ACE‐III) is a well‐validated cognitive screening test, designed to detect Dementia. This work intends to investigate the influence of age, ...gender, and education in Indian population.
Method
Srinivaspura Aging, Neuro Senescence and COGnition (SANSCOG) study and Tata Longitudinal Study on Aging (TLSA) are parallel, prospective, community‐based, cohort studies in India – rural and urban respectively – for comprehensive evaluation of risk and protective factors associated with cognitive changes due to normal ageing, Alzheimer’s disease and other related disorders. 444 and 1344 volunteers were enrolled in TLSA and SANSCOG respectively. ACE‐III was administered on them by trained psychologists. They were classified in four age groups (45– 55, 56–65, 66‐75, and >75 years of age) and six levels for years of education (0‐4, 5‐8, 9‐12, 13‐15, 16‐18, >18). Univariate analysis was performed to study the effect of age, gender, or education, on the ACE‐III total scores. Multivariate analysis was done to study the effects of age, gender, and education on the different cognitive domains of ACE‐III.
Result
No significant differences were observed for ACE‐III among different age groups or gender for individuals enrolled in TLSA, as well as those in SANSCOG. The level of education had a significant effect on ACE‐III as well as all the sub‐domains for SANSCOG participants, but not for TLSA participants. However, age or gender do not show such trends. When the effect of age, gender, and level of education was jointly assessed on these indices, they were found to have significant effects only for visuospatial domain for TLSA participants; and attention and visuospatial domain for SANSCOG participants. Additionally, memory, fluency, language, visuospatial indices of ACE‐III are significantly affected by the age of the participant in SANSCOG.
Conclusion
These results show that age, gender and education of participants can have important effects on performance of ACE‐III and its cognitive sub‐domains. Nevertheless, this is an ongoing work, and currently more participants are being assessed in both the studies who would be followed up longitudinally, which can yield precise conclusive results in future.
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body ...fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
PDF
